Method For Automated Tissue Analysis

ABSTRACT

The invention provides an improved method for identifying and interpreting tissue specimens and/or cells derived from tissue specimens. A panel of cell-based reagents provides a number of readouts of cellular states or biomarkers that together define a profile of a diversity of cellular states or biomarkers in a tissue specimen representing the ‘systems” nature of biology. This cellular profile is interpreted using informatics tools, to identify similarities between specimens, in vivo medical conditions, and suggest options for treating medical conditions.

RELATED APPLICATION

This application is a continuation of U.S. application Ser. No.13/593,663 filed Aug. 24, 2012, which is a continuation of U.S.application Ser. No. 13/346,920 filed Jan. 10, 2012, which is acontinuation of U.S. application Ser. No. 12/227,334 filed Apr. 14,2009, now U.S. Pat. No. 8,114,615, which is the U.S. National Stage ofInternational Application No. PCT/US2007/011865 filed May 17, 2007,published in English, which claims the benefit of U.S. ProvisionalApplication No. 60/801,035, filed on May 17, 2006.

The entire teachings of the above applications are incorporated hereinby reference.

BACKGROUND OF THE INVENTION

The development of capabilities in multicolor fluorescence forapplications in pathology were introduced more than a decade ago [3,6-8] but still have not achieved wide market acceptance. In particular,Dow et al. [7] describe a study where multicolor fluorescence was usedto determine lymphocyte phenotype and activation status in melanomatissue sections through a process of human interactive image analysis.More recently, multicolor fluorescence has been applied in pathology [9]and HistoRx, Inc. (New Haven, Conn.) has commercialized some of theseapproaches. All of these publications and applications describe the useof fluorescence based imaging technology in tissue cell analysis, butare limited in their application and do not address the need tounderstand the systemic or cellular systems biology of a tissue.

High content screening (HCS) and multiparameter HCS technologies weredeveloped to automate cell analysis for drug discovery, HCS technologiesare focused specifically on the measurement of individual targets orpathways in arrays of cultured cells treated with test compounds.However, HCS tools alone do not address the complete workflow of tissuebased cellular systems biology.

Thus, a need exists to provide methods for producing and analyzingcellular systems biology profiles in order to more fully understand thesystemic and complex interaction of cellular biology systems.

SUMMARY OF THE INVENTION

The cell is the simplest living system. Tissues are collections ofspecific cell types forming interacting colonies of cells. Althoughcells and tissues are less complex than a complete organism, theypossess significant functional complexity allowing a detailedunderstanding of many aspects affecting a whole organism, such as thecellular basis of disease, treatment efficacy and potential toxicity oftreatments. Multicolor fluorescence of multiplexed biomarkers coupledwith searchable databases provides the basis for cellular systemsbiology (also referred to herein as systems cell biology) profiling andanalysis.

This invention provides for methods of analyzing and profiling, theanalysis of, and means for profiling, tissue-based cellular systemsbiology. The cellular systems biology approach, including the combiningof traditional histological staining with fluorescent staining toassociate cellular and tissue markers that can be labeled byfluorescence has not been previously applied by others as now describedherein. The use of the transmitted light images based on traditionalhistological stains used by pathologist as a “reference” image or “map”for better interpretation of the multiple fluorescence-based reagents asdescribed herein will increase the acceptance of the systems approach bypathologists and will allow selection of a particular set of biomarkersfor fluorescence analysis.

In one embodiment of the invention, provided is a method for producing acellular systems biology profile of one or more tissue samples. As usedherein, “cellular systems biology” (also referred to herein as systemscell biology), is the investigation of the integrated and interactingnetworks of genes, proteins, and metabolites that are responsible fornormal and abnormal cell functions. Thus, a cellular systems biologyprofile is a systemic characterization of cells in the context of atissue architecture such that the cells have particular characteristicsdependent upon the relationships of different cells within a tissue andthe biological or medical state of the tissue. It is the interactions,relationships, and state of the constituents of cells within a tissuethat gives rise to the cellular systems biology features that are usedto construct a profile. The interrelationships within a cellular systemsbiology profile are defined, for example, either arithmetically (e.g.,ratios, sums, or differences between cellular systems biology featurevalues) or statistically (e.g., hierarchical clustering methods orprincipal component analyses of combinations of cellular systems biologyfeature values). In a particular embodiment, a cellular systems biologyprofile defines the interrelationships between a combination of at leastfive cellular systems biology features collected from cells within oneor more tissue sections from the same sample.

In one embodiment, the invention is directed to a method for producingone or more cellular systems biology profiles for one or more tissuesamples, comprising obtaining at least two sections from one or moretissue samples. At least one section is labeled with a histologicalstain, to produce a histologically stained section. At least one othersection is labeled with a panel of fluorescently labeled reagents toproduce a fluorescently labeled section. In some embodiments thehistologically stained section and the fluorescently stained section arethe same or different. In a particular embodiment, the histologicallystained section and the fluorescently stained section are differentsection. Each fluorescently labeled reagent is specific for a biomarker.As used herein, a “biomarker” is a molecule which provides a measure ofcellular and/or tissue function. For example, and without limitation, abiomarker can be the measure of estrogen receptor expression levels,Her2/neu expression, transcription factor activation, location or amountor activity of a protein, polynucleotide, organelle, and the like, thephosphorylation status of a protein, etc. In one embodiment of theinvention, the panel of fluorescently labeled reagents detects at leastabout four different biomarkers.

The detection of a biomarker in one or more sections is a read-out ofone or more features of the tissue. As used herein, a “feature” is acharacteristic which provides a measurement or series of measurements ofa particular biomarker (which can indicate a biological function) madein time and/or space within cells and tissues. Biological functionsinclude, but are not limited to: protein posttranslational modificationssuch as phosphorylation, proteolytic cleavage, methylation,myristoylation, and attachment of carbohydrates; translocations of ions,metabolites, and macromolecules between compartments within or betweencells; changes in the structure and activity of organelles; andalterations in the expression levels of macromolecules such as codingand non-coding RNAs and proteins, morphology, state of differentiation,and the like. A single biomarker can provide a read-out of more than onefeature. For example, Hoechst dye can be used to detect DNA (e.g., abiomarker), and a number of features of the tissue (e.g., nucleus size,cell cycle stage, number of nuclei, presence of apoptotic nuclei, etc.)can be identified by the DNA detected with the Hoechst dye.

The method further comprises imaging the histologically stained sectionusing a first optical mode, which produces a first set of data andimaging the fluorescently labeled section using a second optical mode,which produces a second set of data. The first set of data and thesecond set of data are analyzed to identify five or more features, suchthat at least one feature is identified in each of the first set of dataand the second set of data. The combination of the five or more featuresgenerates a cellular systems biology profile of the one or more tissuesamples.

In a further embodiment of the invention, the cellular systems biologyprofile is stored in a database for reference, thereby providing areference cellular systems biology profile in a database.

In a further embodiment of the invention, the method for producing acellular systems biology profile of one or more tissue samples furthercomprises producing a cellular systems biology profile of at least oneperipheral blood sample obtained from the same source as the one or moretissue samples

In another embodiment the method for producing a cellular systemsbiology profile of one or more tissue samples comprises obtaining atleast one section from one or more tissue samples. At least one sectionis labeled with a panel of fluorescently labeled reagents to produce afluorescently labeled section, such that each fluorescently labeledreagent is specific for a biomarker. In one embodiment, the panel offluorescently labeled reagents detects at least about four differentbiomarkers, and the detection of a biomarker is a read-out of one ormore features of a cellular systems biology profile. The method furthercomprises imaging the fluorescently labeled section with at least afirst optical mode to produce a first set of data which is analyzed toidentify at least about five or more features, wherein at least onefeature is identified in the first set of data, and wherein thecombination of the five or more features is a cellular systems biologyprofile the one or more tissue samples. Thus, the method produces acellular systems biology profile of the one or more tissue samples. Themethod can further comprises producing a cellular systems biologyprofile of at least one peripheral blood sample obtained from the samesource as the one or more tissue samples.

In a further embodiment of the invention, provided herein is a methodfor producing a cellular systems biology profile of one or more tissuesamples, wherein the tissue sample is profiled for the presence ofcancer, the stage of a cancer, the diagnosis of a cancer, the prognosisof a cancer and/or the absence of a cancer. As will be understood by aperson of skill in the art, different cancers can be classified andstaged according to their pathology. The method described hereinpermits, for example, the confirmation of the presence or absence of acancer, the identification of a cancer, the classification of a cancerstage, the prediction and/or determination of the outcome or prognosisof the cancer, and the response of the cancer to any treatments. Themethod comprises obtaining at least two sections from one or more tissuesamples. At least one section is labeled with a histological stain toproduce a histologically stained section. At least one section islabeled with a panel of fluorescently labeled reagents to produce afluorescently labeled section. Each fluorescently labeled reagent isspecific for a biomarker. The panel of fluorescently labeled reagentscomprises fluorescently labeled reagents which can be selected from thegroup consisting of: i) one or more fluorescently labeled reagentsspecific for at least four cancer cell biomarkers; ii) one or morefluorescently labeled reagents specific for at least four migratoryimmune cell biomarkers; iii) a combination of A) one or morefluorescently labeled reagents specific for at least three cancer cellbiomarkers and B) one or more fluorescently labeled reagents specificfor at least three migratory immune cell biomarkers, and iv)combinations of the above, such that the panel of fluorescently labeledreagents detects at least about four different biomarkers. The detectionof a biomarker is a read-out of one or more features of a cellularsystems biology profile. The method further comprises imaging thehistologically stained section with at least a first optical mode toproduce a first set of data and imaging the fluorescently labeledsection with at least a second optical mode to produce a second set ofdata. The first set of data and second set of data are analyzed toidentify at least about five or more features, such that at least onefeature is identified in each of the first set of data and the secondset of data. The combination of the five or more features is a cellularsystems biology profile of the one or more tissue samples, and thus themethod produces a cellular systems biology profile of the one or moretissue samples, wherein the tissue sample is profiled for the presenceof a cancer, the stage of a cancer, the diagnosis of a cancer, theprognosis of a cancer or the absence of a cancer. In one embodiment, theone or more tissue samples is selected from the group consisting asuspected or known cancerous tissue, a lymph node, and a combinationthereof.

In a still further embodiment of the invention, the method for producinga cellular systems biology profile of one or more tissue samples,wherein the tissue sample is profiled for the presence of cancer, thestage of a cancer, the diagnosis of a cancer, the prognosis of a cancerand/or the absence of a cancer further comprises producing a cellularsystems biology profile of at least one peripheral blood sample obtainedfrom the same source as the one or more tissue samples

In another embodiment of the invention, provided herein is a method forproducing a cellular systems biology profile of one or more tissuesamples, wherein the tissue sample is profiled for the presence,severity or absence of a tissue toxicity. The method comprises obtainingat least two sections from one or more tissue samples. At least onesection labeled with a histological stain to produce a histologicallystained section and at least one section is with a panel offluorescently labeled reagents to produce a fluorescently labeledsection. Each fluorescently labeled reagent is specific for a biomarker.The panel of fluorescently labeled reagents comprises a set offluorescently labeled reagents selected from the group consisting of i)one or more fluorescently labeled reagents specific for cell metabolismbiomarkers, ii) one or more fluorescently labeled reagents specific forDNA damage biomarkers, iii) one or more fluorescently labeled reagentsspecific for cell morphology biomarkers, iv) one or more fluorescentlylabeled reagents specific for DNA damage biomarkers, v) one or morefluorescently labeled reagents specific for cell differentiationbiomarkers, vi) one or more fluorescently labeled reagents specific forstress-induced transcription activation or inhibition biomarkers, vii) aone or more fluorescently labeled reagents specific for phosphorylationstatus of stress kinase biomarkers, viii) one or more fluorescentlylabeled reagents specific for apoptosis or necrosis biomarkers, ix) oneor more fluorescently labeled reagents specific for cytoskeletonbiomarkers, x) one or more fluorescently labeled reagents specific fororganelle biomarkers, xi) one or more f fluorescently labeled reagentsspecific for presence or activation of immune cell biomarkers, and xii)combinations thereof, such that the panel of fluorescently labeledreagents detects at least about four different biomarkers, and whereinthe detection of a biomarker is a read-out of one or more features of acellular systems biology profile. The histologically stained section isimaged with at least a first optical mode to produce a first set ofdata. The fluorescently labeled section is imaged with at least a secondoptical mode to produce a second set of data. The method furthercomprises analyzing the first set of data and second set of data toidentify at least about five or more features, wherein at least onefeature is identified in each of the first set of data and the secondset of data. The combination of the five or more features is a cellularsystems biology profile of the one or more tissue samples. Thus, themethod produces a cellular systems biology profile of the one or moretissue samples, wherein the tissue sample is profiled for the presence,severity or absence of a tissue toxicity. In one embodiment, the one ormore tissue samples is one or more liver tissue samples.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing will be apparent from the following more particulardescription of example embodiments of the invention, as illustrated inthe accompanying drawings in which like reference characters refer tothe same parts throughout the different views. The drawings are notnecessarily to scale, emphasis instead being placed upon illustratingembodiments of the present invention.

FIG. 1 are examples of slides for Tissue Profiling. FIG. 1A is Sample#01, which represents a slide that combines a tissue section labeledwith H&E stain, and a sequential section labeled with fluorescent tagsfor specific biomarkers. FIG. 1B is Sample #02, which illustrates aslide with an H&E stained section, a fluorescent labeled section andsome cells isolated from patient tissue and labeled with fluorescenttags (pictures of sections and cells are all enlarged for illustrativepurposes).

FIG. 2 is a schematic of systems cell biology (also referred to hereinas cellular systems biology) profiling, which involves the analysis of adiverse set of cellular biomarkers used to identify features to create aprofile. FIG. 2A represent cells from a patient that are, e.g., healthy,diseased or being treated or have been treated with a drug. FIG. 2Bschematically represents the analysis of a set of biomarkers. FIG. 2Crepresents a panel of cellular biomarkers used to produce cellularsystems biology profile. These profiles are stored in a database(schematically shown in FIG. 2D), which can be used a referencedatabase. Comparison of a patient profile with reference profiles isused e.g., as a predictive tool, or to associate a biomarker, feature ora profile with a specific medical condition, or to evaluate newprofiles.

FIG. 3 is a schematic illustrating the interrelation of systems cellbiology which captures enough complexity to correlate biomarkers withhigher level organ and organism effects, while allowing high throughputand cost-effective profiling. Cellular systems biology and systemsbiology are based on the interactions and relationships between thefundamental components of living systems represented by the “-omics” anda selection of specific cellular biomarkers are obtained from acombination of genomics, proteomics and metabolomics, in the context ofthe cells studied (cellomics).

FIG. 4 is a schematic of how a cell integrates the many processesillustrated, such as gene expression, energy metabolism, etc. to yieldnormal functions. Diseases result from the dysregulation of one or moreof these cellular processes which often results in complex symptoms.Many of these processes share pathways, signals and proteins andtherefore should be investigated as part of the cell system (includingthe collection of cells of different types in tissues).

FIG. 5 illustrate examples of biomarkers for use in patient tissueprofiling selected from function classes that include, for example: (A)Stress Pathways; (B) Organelle Function; (C) Cell Cycle; (D) Morphology;(E) Apoptosis; and (F) DNA Damage, as well as micro RNA, and migratoryimmune cells. Specific combinations of biomarkers are selected foranalysis of particular disease conditions, as described herein.

FIG. 6 is an example of the multiplexed labeling of cells with a panelof biomarkers such as would be used in tissue sections. Labels aremultiplexed in tissue which allows analysis of correlations betweenbiomarker activation within the same tissue, and to reduce the number ofsections that must be prepared and analyzed. In a particular embodiment,at least four or more biomarkers are analyzed in each section.

FIG. 7 is a schematic flow chart of the process of creating a referenceprofile database as described in one embodiment of the invention. Box 1:Sequential tissue sections are prepared and mounted. Box 2(a): Onesection is labeled with H&E stain for transmitted light imaging orreview. Box 2(b): A second section is labeled with a panel offluorescent labels to measure biomarkers. Boxes 3(a & b): Sections areimaged or viewed for interpretation. Boxes 4(a & b): Sections areanalyzed and/or interpreted to create data. Box 5: Data from thesequential sections are compared and combined. Box 6: The cellularsystems profile is added to database. Box 7: Tissue profiles in databaseare clustered to identify similarities. Box 8: Profile classes areidentified. Box 9: Correlations between systems profiles andhistological data are used to build a classifier which is stored in thedatabase.

FIG. 8 is a flow chart illustrating the process of analyzing andclassifying tissue, e.g., from a patient.

FIGS. 9A-I is a flow chart illustrating the overall process forautomated tissue profiling in one embodiment of the invention. FIG. 9(A)Process starts with reference tissue with know medical history. FIG.9(B) Profiles from fluorescence analysis are combined with results fromhuman interpretation of stained sections along with medical history;FIG. 9(C) to build a classifier and FIG. 9(D) populate a referencedatabase. FIG. 9(E) Patient tissues are FIG. 9(F) prepared, analyzed andFIG. 9(G) classified to identify FIG. 9(H) similarities to other patientprofiles (patient stratification) and FIG. 9(I) to make predictionsregarding medical conditions, or medical outcomes.

FIG. 10 is a flow chart of the process for selecting biomarkers for acancer tissue profiling panel. Box (1) Normal tissue from Patient is(Box 2) analyzed by Gene Expression profiling. Box (3) A sample of tumortissue from the same patient is (Box 4) analyzed by Gene ExpressionProfiling and is (Box 5) staged in the traditional manner. This combinedinformation, comparing “normal” tissue with patient tumor tissue is (Box6) used to identify potential biomarkers. Box (7) Gene products areprioritized based on known reference points including Her2/Neu and thenantibodies acquired or produced to create test panels (Box 8). Thedesign of the biomarker panel is based on the selection of combinationsof cancer cell biomarkers that are multiplexed for fluorescence-basedimmunohistochemistry (IHC).

FIG. 11 is an overview of one embodiment of the invention. Tissuesamples from a patient (A) which could include healthy tissue, tumortissue, other diseased tissue or a blood specimen are processed bystandard methods for mounting on slides (B) either as individualsections or as tissue microarrays. Slides are imaged on a microscope orother imaging system (C). Images are interpreted either by a pathologistor through the application of image analysis algorithms to produce data(D) which can be stored in a database. The combination of the data froma single specimen forms a cellular systems profile of that specimen.Data from multiple cellular systems profiles are analyzed usingstatistical methods including cluster analysis, principle componentanalysis, and other multifactorial methods to identify similaritiesbetween profiles which can be represented in a clustered heat map (E),identify patterns within a profile that indicate a certain biological ormedical state, and to classify tissue status based on similarity inprofiles. The information provided by cellular systems biology profilingis used by the physician or scientist (F) to better understand thebiology or progression of a disease or biological condition, to moreprecisely stratify patients in a clinical trial and/or to optimize atherapeutic approach (G) to treating a condition.

DETAILED DESCRIPTION OF THE INVENTION

“Cellular systems biology” is defined as the investigation of theintegrated and interacting networks of genes, proteins, and metabolicreactions that give rise to function and life. Cells in tissues, ascomplex systems, exhibit properties that are not anticipated from theanalysis of individual components, known as emergent properties thatrequire analysis of many factors to characterize cellular states. Taylorand Giuliano [10] describe the application of in vitro cell systemsanalysis to drug discovery. In this analysis, correlation betweenmeasurements in individual cells was required to identify and interpretcell responses to drug treatment.

“Cellular systems biology features” are defined as a data measurementsor a series of measurements of a particular biological function(typically evidenced by the presence, absence and/or level of one ormore biomarkers) made in time and/or space within cells and tissues.Examples of biological functions include, but are not limited to:protein posttranslational modifications such as phosphorylation,proteolytic cleavage, methylation, myristoylation, and attachment ofcarbohydrates; translocations of ions, metabolites, and macromoleculesbetween compartments within or between cells; changes in the structureand activity of organelles; and alterations in the expression levels ofmacromolecules such as coding and non-coding RNAs and proteins.

Cellular Systems Biology analysis of cells in tissues makes use of someof the cell analysis algorithms developed for High Content Screening(HCS). “HCS” is defined as a technology platform designed to measure thetemporal and spatial activities of genes, proteins, and other cellularconstituents in living cells in response to drug treatment (Giuliano, K.A.; Haskins, J. R.; Taylor, D. L., Advances in high content screeningfor drug discovery. ASSAY and Drug Development Technologies 2003, 1,565-577). HCS and multiparameter HCS were developed to measureindividual targets or pathways in arrays of cultured cells in responseto drug treatment. However, as described herein, HCS image analysistools can also be used to extract data from cells in tissues as part ofa cellular systems biology profiling approach that would enable thecharacterization of complex and emergent properties that arise in livingcells and tissue. In addition, numerous other image analysis softwarepackages, including those that are supplied with microscope slidescanning systems could be applied to extract cellular features fromimages of tissues to build a cellular systems biology profile.

“Cellular systems biology profiles” are defined as theinterrelationships between combination of at least about five cellularsystems biology features collected from cells within one or more tissuesections from the same sample. These interrelationships are calculatedeither arithmetically (e.g., ratios, sums, or differences betweencellular systems biology feature values) or statistically (e.g.,hierarchical clustering methods or principal component analyses ofcombinations of cellular systems biology feature values). Cellularsystems biology profiles can be used to understand the complex responseof cells and tissues to disease and various treatments by characterizingthe emergent properties of the cellular systems response.

“Emergent properties” refers to the arising of novel and coherentstructures, patterns, and properties during the process ofself-organization in complex systems (Goldstein, Jeffrey (1999),“Emergence as a Construct: History and Issues”, Emergence: Complexityand Organization 1: 49-72). The emergent properties of cells and tissues(e.g., growth and division, transformation to a tumor phenotype, etc.)cannot begin to be defined until a systemic analysis of complex cellularfunction is undertaken. Emergent properties are not anticipated from theanalysis of individual components, but require analysis of many factorsto characterize cellular states.

Although the analysis of single, individual features in tissue sectionshas value, the application of a “systems approach” wherein, as providedherein, multiple features (e.g., at least about four features, at leastabout five features, at least about six features, at least about 7-12features, or more), of a tissue are analyzed, enables a more precisedetermination of the state of the cells, the tissues, and the organismas a whole. Furthermore, this approach facilitates, for example, theautomation of tissue analysis, and the production of tissue profiles formore precise tumor staging, personalized treatments, evaluation oftreatment efficacy, and early indication of side effects, as well asimproved analyses in animal toxicology studies in drug discovery.

Systems Biology and Cellular Systems Biology: The cell is the simplestliving system. Tissues are collections of specific cell types forminginteracting colonies of cells. Although cells and tissues are lesscomplex than a complete organism, they possess significant functionalcomplexity allowing a detailed understanding of the cellular basis ofdisease, treatment efficacy and potential toxicity of treatments.Multicolor fluorescence of multiplexed biomarkers coupled withsearchable databases provides the basis for systems cell analysis.

Prior to this invention, the analysis and profiling of tissue-basedcellular systems biology has not been described. The cellular systemsbiology approach, including the combining of traditional histologicalstaining with fluorescent staining to associate cellular and tissuemarkers that can be labeled by fluorescence has not been previously doneby others as now described herein. The use of the transmitted lightimages based on traditional (non-fluorescent) histological stains usedby pathologist as a “reference” image or “map” for better interpretationof the multiple fluorescence-based reagents as described herein willincrease the acceptance of the systems approach by pathologists and willallow the selection of a specific set of biomarkers for fluorescenceanalysis.

In one embodiment of the invention, provided is a method for producing acellular systems biology profile of one or more tissue samples. As usedherein, “cellular systems biology” (also referred to herein as systemscell biology), is the investigation of the integrated and interactingnetworks of genes, proteins, and metabolites that are responsible fornormal and abnormal cell functions. Thus, a cellular systems biologyprofile is a systemic characterization of cells in the context of atissue architecture such that the cells have particular characteristicsdependent upon the relationships of different cells within a tissue andthe biological or medical state of the tissue. It is the interactions,relationships, and state of the constituents of cells within a tissuethat gives rise to the cellular systems biology features that are usedto construct a profile. The interrelationships within a cellular systemsbiology profile are defined or calculated, for example, eitherarithmetically (e.g., ratios, sums, or differences between cellularsystems biology feature values) or statistically (e.g., hierarchicalclustering methods or principal component analyses of combinations ofcellular systems biology feature values). In a particular embodiment, acellular systems biology profile defines the interrelationships betweena combination of at least about five cellular systems biology featurescollected from cells within one or more tissue sections from the samesample. In another embodiment, a cellular systems biology profile is thecombination of at least about six, seven, eight, nine, ten, eleven,twelve, or more features.

In one embodiment of the invention, the method comprises obtaining atleast two sections from one or more tissue samples. Any suitable tissuesample can be used in the methods described herein. For example, thetissue can be epithelium, muscle, organ tissue, nerve tissue, tumortissue, and combinations thereof. In one embodiment, blood is not atissue sample. Samples of tissue can be obtained by any standard means(e.g., biopsy, core puncture, dissection, and the like, as will beappreciated by a person of skill in the art). At least one section islabeled with a histological stain, to produce a histologically stainedsection. As used in the invention described herein, histological stainscan be any standard stain as appreciated in the art, including but notlimited to, alcian blue, Fuchsin, haematoxylin and eosin (H&E), Massontrichrome, toluidine blue, Wright's/Giemsa stain, and combinationsthereof. As will be appreciated by a person of skill in the art,traditional histological stains are not fluorescent. At least one othersection is labeled with a panel of fluorescently labeled reagents toproduce a fluorescently labeled section. As used in the inventiondescribed herein, the panel of fluorescently labeled reagents comprisesa number of reagents, such as fluorescently labeled antibodies,fluorescently labeled peptides, fluorescently labeled polypeptides,fluorescently labeled aptamers, fluorescently labeled oligonucleotides(e.g. nucleic acid probes, DNA, RNA, cDNA, PNA, and the like),fluorescently labeled chemicals and fluorescent chemicals (e.g., Hoechst33342, propidium iodide, Draq-5, Nile Red, fluorescently labeledphalloidin), and combinations thereof. Each fluorescently labeledreagent is specific for at least one biomarker. As used herein, a“biomarker” is a molecule which provides a measure of cellular and/ortissue function. For example, and without limitation, a biomarker can bethe measure of receptor expression levels, (e.g., estrogen receptorexpression levels, Her2/neu expression); transcription factoractivation; location or amount or activity of a protein, polynucleotide,organelle, and the like; the phosphorylation status of a protein, etc.In one embodiment, a biomarker is a nucleic acid (e.g., DNA, RNA,including micro RNAs, snRNAs, mRNA, rRNA, etc.), a receptor, a cellmembrane antigen, an intracellular antigen, and extracellular antigen, asignaling molecule, a protein, and the like. In one embodiment of theinvention, the panel of fluorescently labeled reagents detects at leastabout four different biomarkers. In another embodiment of the invention,the panel of fluorescently labeled reagents detects at least about fourto about six, to about ten, to about twelve different biomarkers ormore. In another embodiment of the invention, the panel of fluorescentlylabeled reagents detects at least about three different biomarkers. In afurther embodiment, each fluorescently labeled reagent has differentfluorescent properties, which are sufficient to distinguish thedifferent fluorescently labeled reagents in the panel.

The detection of a biomarker in one or more sections is a read-out ofone or more features of a cellular systems biology profile. As usedherein, a “feature” is a characteristic which provides a measurement orseries of measurements of a particular biomarker (which can indicate abiological function) made in time and/or space within cells and tissues.Biological functions include, but are not limited to: proteinposttranslational modifications such as phosphorylation, proteolyticcleavage, methylation, myristoylation, and attachment of carbohydrates;translocations of ions, metabolites, and macromolecules betweencompartments within or between cells; changes in the structure andactivity of organelles; and alterations in the expression levels ofmacromolecules such as coding and non-coding RNAs and proteins,morphology, state of differentiation, and the like. A single biomarkercan provide a read-out of more than one feature. For example, Hoechstdye detects DNA, which is an example of a biomarker. A number offeatures can be identified by the Hoechst dye in the tissue sample suchas nucleus size, cell cycle stage, number of nuclei, presence ofapoptotic nuclei, etc.

The method further comprises imaging the histologically stained sectionusing a first optical mode, which produces a first set of data andimaging the fluorescently labeled section using a second optical mode,which produces a second set of data. As will be appreciated by theperson of skill in the art, as used in the invention described herein,the optical mode for imaging can be any mode suitable for this use,e.g., transmitted light microscopy, fluorescence light microscopy, widefield microscopy, confocal microscopy, and combinations thereof, asappropriate. In one embodiment, the data produced in either or both ofthe first set of data and second set of data can be digital data. Thefirst set of data and the second set of data are analyzed to identifyfive or more features, such that at least one feature is identified inthe first set of data and at least one feature is identified in thesecond set of data. The combination of the five or more featuresgenerates a cellular systems biology profile of the one or more tissuesamples.

In one embodiment of the invention, the imaging procedures areautomated. Furthermore, analyzing the data can be performed manually, byautomation or a combination thereof. As will be appreciated by a personof skill in the art, imaging a histologically stained section andimaging a fluorescently labeled section can be done sequentially orsimultaneously. In addition, histological labeling and fluorescentlabeling can be done sequentially or simultaneously. In someembodiments, after obtaining one or more sections from a tissue sample,the method is wholly automated.

In a further embodiment of the invention, the method further comprisescomparing the cellular systems biology profiles of two or more tissuesamples in order to identify similarities, differences, or combinationsthereof, of the two or more tissue samples. In one embodiment, the twoor more tissue samples are serial sections from a single tissuespecimen. Serial sections of a single tissue sample are tissue sectionswhich were adjacent to each other in the preparation of two or moresections from a tissue sample.

In one embodiment of the invention, the one or more tissue samples areisolated from one or more animals. For example, in one embodiment, theone or more animals are one or more humans. In a particular embodiment,one or more tissue samples are isolated from a human patient at one ormore time points, such that at least one tissue sample is isolated fromeach time point from the same patient.

In another embodiment of the invention, the panel of fluorescentlylabeled reagents indicate the presence, amount, location, activity,distribution, or combination thereof, of the biomarkers in thefluorescently labeled section. The location of a biomarker can beintracellular, extracellular, within specific intracellular locations,at specific extracellular locations, and combinations thereof. Activityof a biomarker can be the activation state of the biomarker (such asindicated, e.g., by its phosphorylation state, conformation state, orintracellular location, and the like).

In a further embodiment of the invention, the cellular systems biologyprofile is stored in a database for reference, thereby providing areference cellular systems biology profile in a database. In oneembodiment, the database is a computer. In another embodiment, thedatabase is stored on a server. In one embodiment, the referencecellular systems biology profile in the database is compared with acellular systems biology profile of one or more further samples. Thispermits the identification of similarities, differences, or acombination thereof, of the cellular systems biology profile of the oneor more further samples and the reference cellular systems biologyprofile. Various methods can be used to compare the cellular systemsbiology profile of the one or more further samples and the cellularsystems biology profile in the database, such as by graphical display,cluster analysis, or statistical measure of correlation and combinationsthereof.

In a further embodiment of the invention, the method for producing acellular systems biology profile of one or more tissue samples furthercomprises producing a cellular systems biology profile of at least oneblood sample obtained from the same source as the one or more tissuesamples. In one embodiment, the blood sample is a peripheral bloodsample. Peripheral blood is the cellular components of blood, consistingof red blood cells, white blood cells, and platelets, which are foundwithin the circulating pool of blood and not sequestered within thelymphatic system, spleen, liver, or bone marrow. The method comprisesobtaining at least one blood sample smear from at least one peripheralblood sample from the same source as the one or more tissue samples. Asused in the invention described herein, peripheral blood samples can beobtained by any standard procedure. The at least one blood sample smearis labeled with a panel of fluorescently labeled reagents to produce afluorescently labeled blood sample smear, wherein each fluorescentlylabeled reagent is specific for a biomarker. In one embodiment, thepanel of fluorescently labeled reagents detects at least about fourdifferent biomarkers. The detection of a biomarker is a read-out of oneor more features of a cellular systems biology profile. The methodfurther comprises imaging the fluorescently labeled blood sample smearwith at least a third optical mode, such that the imaging produces athird set of data. The third set of data is analyzed to identify atleast about five or more features, wherein the five or more features isa cellular systems biology profile of the at least one blood samplesmear. This method produces a cellular systems biology profile of the atleast one peripheral blood sample obtained from the same source as theone or more tissue samples. In one embodiment, the at least oneperipheral blood sample is taken at the same or different time point asthe one or more tissue samples are obtained. In another embodiment, morethan one peripheral blood sample is taken at different time points, andthe cellular systems biology profiles of the more than one peripheralblood samples are compared.

In another embodiment of the invention, the method for producing acellular systems biology profile of one or more tissue samples furthercomprises producing a cellular systems biology profile of one or moreperipheral blood samples obtained from the same source as the one ormore tissue samples. The method comprises obtaining at least two bloodsample smears from one or more peripheral blood samples. At least oneblood sample smear is labeled with a histological stain to produce ahistologically stained blood sample smear. In addition, at least oneblood sample smear is labeled with a panel of fluorescently labeledreagents to produce a fluorescently labeled blood sample smear. Eachfluorescently labeled reagent is specific for a biomarker, and whereinthe panel of fluorescently labeled reagents detects at least about fourdifferent biomarkers, and wherein the detection of a biomarker is aread-out of one or more features of a cellular systems biology profile.The histologically stained blood sample smear is imaged with at least athird optical mode to produce a third set of data. The fluorescentlylabeled blood sample smear is imaged with at least a fourth optical modeto produce a fourth set of data. The third set of data and the fourthset of data are analyzed to identify at least about five or morefeatures, wherein at least one feature is identified in each of thethird set of data and the fourth set of data, such that the combinationof the five or more features is a cellular systems biology profile ofthe one or more blood sample smears. Thus the method produces a cellularsystems biology profile of the one or more peripheral blood samplesobtained from the same source as the one or more tissue samples. Asdiscussed above, in one embodiment, the one or more peripheral bloodsamples are taken at the same or different time point as the one or moretissue samples are obtained. Furthermore, in another embodiment, whenone or more peripheral blood samples are taken at different time points,the cellular systems biology profiles of the one or more peripheralblood samples are compared.

In an additional embodiment of the invention, provided herein is amethod for producing a cellular systems biology profile of one or moretissue samples. The method comprises obtaining at least one section fromone or more tissue samples. At least one section is labeled with a panelof fluorescently labeled reagents to produce a fluorescently labeledsection, such that each fluorescently labeled reagent is specific for abiomarker. In one embodiment, the panel of fluorescently labeledreagents detects at least about four different biomarkers, and thedetection of a biomarker is a read-out of one or more features of acellular systems biology profile. The method further comprises imagingthe fluorescently labeled section with at least a first optical mode toproduce a first set of data which is analyzed to identify at least aboutfive or more features, wherein at least one feature is identified in thefirst set of data, and wherein the combination of the five or morefeatures is a cellular systems biology profile the one or more tissuesamples. Thus, the method produces a cellular systems biology profile ofthe one or more tissue samples. In a further embodiment, the methodfurther comprises producing a cellular systems biology profile of atleast one peripheral blood sample obtained from the same source as theone or more tissue samples. The method comprises obtaining at least oneblood sample smear from at least one peripheral blood sample. The atleast one blood sample smear is labeled with a panel of fluorescentlylabeled reagents to produce a fluorescently labeled blood sample smear,such that each fluorescently labeled reagent is specific for abiomarker. The panel of fluorescently labeled reagents detects at leastabout four different biomarkers, and the detection of a biomarker is aread-out of one or more features of a cellular systems biology profile.The method further comprises imaging the fluorescently labeled bloodsample smear with at least a second optical mode to produce a second setof data. The second set of data is analyzed to identify at least aboutfive or more features, such that the five or more features is a cellularsystems biology profile of the at least one blood sample smear. Thus,the method produces a cellular systems biology profile of the at leastone peripheral blood sample obtained from the same source as the one ormore tissue samples. In an optional embodiment, the method furthercomprises labeling at least one blood sample smear with a histologicalstain to produce a histologically stained blood sample smear. Thehistologically stained blood sample smear is imaged to produce anadditional set of data which is analyzed to identify at least onefeature, wherein the combination of the five or more features identifiedin the combination of the histologically stained blood sample smear andthe fluorescently stained blood sample smear is a cellular systemsbiology profile of the one or more blood sample smears.

In a further embodiment of the invention, provided herein is a methodfor producing a cellular systems biology profile of one or more tissuesamples, wherein the tissue sample is profiled for the presence ofcancer, the stage of a cancer, the diagnosis of a cancer, the prognosisof a cancer and/or the absence of a cancer. As will be understood by aperson of skill in the art, different cancers can be classified andstaged according to their pathology. The method described hereinpermits, for example, the confirmation of the presence or absence of acancer, the identification of a cancer, the classification of a cancerstage, the prediction and/or determination of the outcome or prognosisof the cancer, and the response of the cancer to any treatments. Themethod comprises obtaining at least two sections from one or more tissuesamples. At least one section is labeled with a histological stain toproduce a histologically stained section. At least one section islabeled with a panel of fluorescently labeled reagents to produce afluorescently labeled section. Each fluorescently labeled reagent isspecific for a biomarker. The panel of fluorescently labeled reagentscomprises fluorescently labeled reagents which can be selected from thegroup consisting of: i) a set of fluorescently labeled reagents specificfor at least four cancer cell biomarkers; ii) a set of fluorescentlylabeled reagents specific for at least four migratory immune cellbiomarkers; iii) a combination of A) a set of fluorescently labeledreagents specific for at least three cancer cell biomarkers and B) a setof fluorescently labeled reagents specific for at least three migratoryimmune cell biomarkers, and iv) combinations of the above, such that thepanel of fluorescently labeled reagents detects at least about fourdifferent biomarkers. The detection of a biomarker is a read-out of oneor more features of a cellular systems biology profile. The methodfurther comprises imaging the histologically stained section with atleast a first optical mode to produce a first set of data and imagingthe fluorescently labeled section with at least a second optical mode toproduce a second set of data. The first set of data and second set ofdata are analyzed to identify at least about five or more features, suchthat at least one feature is identified in each of the first set of dataand the second set of data. The combination of the five or more featuresis a cellular systems biology profile of the one or more tissue samples,and thus the method produces a cellular systems biology profile of theone or more tissue samples, wherein the tissue sample is profiled forthe presence of a cancer, the stage of a cancer, the diagnosis of acancer, the prognosis of a cancer or the absence of a cancer. In oneembodiment, the cancer is breast cancer.

In a further embodiment, the fluorescently labeled reagents specific forcancer cell biomarkers detect cancer cell markers such as HER2/neu,estrogen receptor (ER), Ki-67, Cox-2, p16 and the like. In anotherembodiment, the fluorescently labeled reagents specific for migratoryimmune cell biomarkers detect migratory immune cell biomarkers such asNK cell biomarkers, LAK cell biomarkers, TRAIL, PD1, biomarkers ofimmune cell apoptosis, and the like. In an additional embodiment, afeature is a ratio of different migratory immune cell subtypes asdetected by the migratory immune cell biomarkers, such that the ratio isindicative of the presence of a cancer, the stage of cancer, thediagnosis of a cancer, the prognosis of a cancer, the absence of acancer and combinations thereof.

In a further embodiment, the one or more tissue samples is selected fromthe group consisting a suspected or known cancerous tissue, a lymphnode, and a combination thereof.

Migratory immune cells are typically white blood cells (leukocytes). Inone embodiment, examples of migratory immune cell biomarkers include,without limitation, the percentage and ratios of specific migratoryimmune cells in tumors, tumor draining lymph nodes, non-sentinel lymphnodes and peripheral blood. Examples of migratory immune cells in normalblood include: (1) lymphocytes (25% of white blood cells) which includesT-cells (distinct sub-types), B-cells (distinct sub-types), and naturalkiller (NK) cells; (2) Neutrophils (65% of white blood cells); (3)Eosinophils (4% of white blood cells) and (4) Monocytes (6% of whiteblood cells), which includes macrophages (distinct sub-types). In oneembodiment, the percentage ranges of immune cells in tissues forcellular systems biology profiling comprise one or more of thefollowing: lymphocytes from about 1% to about 90% (with distinctsub-types within this percentage, as will be recognized by a person ofskill in the art); neutrophils from about 1% to about 90%; eosinophilsfrom about 0.01% to about 50%; monocytes from about 0.01% to about 50%(with distinct sub-types within this percentage, as will be recognizedby a person of skill in the art). In another embodiment of theinvention, the ranges of ratios of immune cells in tissues for cellularsystems biology profiling comprise one or more of the following: T-celllymphocytes/B-cell lymphocytes from about 0.1 to about 1000; dendriticcells/lymphocytes from about 0.01 to about 1000; macrophages/lymphocytesfrom about 0.01 to about 1000; lymphocyte sub-set/lymphocyte sub-setfrom about 0.01 to about 1000.

In a still further embodiment of the invention, the method for producinga cellular systems biology profile of one or more tissue samples,wherein the tissue sample is profiled for the presence of cancer, thestage of a cancer, the diagnosis of a cancer, the prognosis of a cancerand/or the absence of a cancer further comprises producing a cellularsystems biology profile of at least one peripheral blood sample obtainedfrom the same source as the one or more tissue samples. The methodcomprises obtaining at least one blood sample smear from at least oneperipheral blood sample and labeling the at least one blood sample smearwith a panel of fluorescently labeled reagents to produce afluorescently labeled blood sample smear. Each fluorescently labeledreagent is specific for a biomarker, and the panel of fluorescentlylabeled reagents detects at least about four different biomarkers. Thedetection of a biomarker is a read-out of one or more features of acellular systems biology profile. The method further comprises imagingthe fluorescently labeled blood sample smear with at least a thirdoptical mode to produce a third set of data. The third set of data isanalyzed to identify five or more features, wherein the five or morefeatures is a cellular systems biology profile of the at least one bloodsample smear. Thus, the method produces a cellular systems biologyprofile of the at least one peripheral blood sample obtained from thesame source as the one or more tissue samples. In one embodiment, the atleast one peripheral blood sample is taken at the same or different timepoint as the one or more tissue samples are obtained. In anotherembodiment, more than one peripheral blood sample is taken at differenttime points, and the cellular systems biology profiles of the more thanone peripheral blood samples are compared.

In a still further embodiment of the invention, the method for producinga cellular systems biology profile of one or more tissue samples,wherein the tissue sample is profiled for the presence of cancer, thestage of a cancer, the diagnosis of a cancer, the prognosis of a cancerand/or the absence of a cancer further comprises producing a cellularsystems biology profile of at least one peripheral blood sample obtainedfrom the same source as the one or more tissue samples. The methodcomprises obtaining at least two blood sample smears from one or moreperipheral blood samples and labeling at least one blood sample smearwith a histological stain to produce a histologically stained bloodsample smear. The method further comprises labeling at least one bloodsample smear with a panel of fluorescently labeled reagents to produce afluorescently labeled blood sample smear, such that each fluorescentlylabeled reagent is specific for a biomarker. The panel of fluorescentlylabeled reagents detects at least about four different biomarkers, andthe detection of a biomarker is a read-out of one or more features of acellular systems biology profile. The method also comprises imaging thehistologically stained blood sample smear with at least a third opticalmode to produce a third set of data and imaging the fluorescentlylabeled blood sample smear with at least a fourth optical mode toproduce a fourth set of data. The third set of data and the fourth setof data are analyzed to identify at least about five or more features,wherein at least one feature is identified in each of the third set ofdata and the fourth set of data, such that the combination of the fiveor more features is a cellular systems biology profile of the one ormore blood sample smears. Thus, the method produces a cellular systemsbiology profile of one the or more peripheral blood samples obtainedfrom the same source as the one or more tissue samples, wherein thetissue sample is profiled for the presence or absence of a cancer, thestage of a cancer, the diagnosis of a cancer, the prognosis of a cancerof the absence of a cancer. In one embodiment, the one or moreperipheral blood samples are taken at the same or different time pointsas the one or more tissue samples are obtained. In another embodiment,more than one peripheral blood samples are taken at different timepoints, and the cellular systems biology profile of the more than oneperipheral blood samples are compared.

In another embodiment of the invention, provided herein is a method forproducing a cellular systems biology profile of one or more tissuesamples, wherein the tissue sample is profiled for the presence,severity or absence of a tissue toxicity. The method comprises obtainingat least two sections from one or more tissue samples. At least onesection labeled with a histological stain to produce a histologicallystained section and at least one section is with a panel offluorescently labeled reagents to produce a fluorescently labeledsection. Each fluorescently labeled reagent is specific for a biomarker.The panel of fluorescently labeled reagents comprises a set offluorescently labeled reagents selected from the group consisting of i)a set of fluorescently labeled reagents specific for cell metabolismbiomarkers, ii) a set of fluorescently labeled reagents specific for DNAdamage biomarkers, iii) a set of fluorescently labeled reagents specificfor cell morphology biomarkers, iv) a set of fluorescently labeledreagents specific for DNA damage biomarkers, v) a set of fluorescentlylabeled reagents specific for cell differentiation biomarkers, vi) a setof fluorescently labeled reagents specific for stress-inducedtranscription activation or inhibition biomarkers, vii) a set offluorescently labeled reagents specific for phosphorylation status ofstress kinase biomarkers, viii) a set of fluorescently labeled reagentsspecific for apoptosis or necrosis biomarkers, ix) a set offluorescently labeled reagents specific for cytoskeleton biomarkers, x)a set of fluorescently labeled reagents specific for organellebiomarkers, xi) a set of fluorescently labeled reagents specific forpresence or activation of immune cell biomarkers, and xii) combinationsthereof, such that the panel of fluorescently labeled reagents detectsat least about four different biomarkers, and wherein the detection of abiomarker is a read-out of one or more features of a cellular systemsbiology profile. The histologically stained section is imaged with atleast a first optical mode to produce a first set of data. Thefluorescently labeled section is imaged with at least a second opticalmode to produce a second set of data. The method further comprisesanalyzing the first set of data and second set of data to identify atleast about five or more features, wherein at least one feature isidentified in each of the first set of data and the second set of data.The combination of the five or more features is a cellular systemsbiology profile of the one or more tissue samples. Thus, the methodproduces a cellular systems biology profile of the one or more tissuesamples, wherein the tissue sample is profiled for the presence,severity or absence of a tissue toxicity. In one embodiment, the one ormore tissue samples is one or more liver tissue samples.

As will be understood by a person of skill in the art, the methods ofthe invention as described herein can be used in many applications. Theinvention advances technologies currently in practice, some of which areoutlined herein.

Staining and Transmitted Light Imaging in Pathology, Toxicology andPersonalized Medicine: Standard histological methods for staining andimaging of tissue sections in Pathology, and Toxicology were developedto meet the needs of pathologists and toxicologists to view the sectionsand make a determination based on experience and knowledge. Stains suchas H&E (Hematoxylin and Eosin), congo red, Gram bacterial stain andothers provide the means to label various cell types and structures, tofacilitate interpretation. Although experienced pathologists can learnto interpret the staining patterns, efforts to automate theinterpretation of the patterns have met with great difficulty.Fluorescent labeling technologies, especially when coupled withantibodies or other molecularly specific biomarkers or tags such asaptamers, allow for very specific labeling of cellular components, highsignal to background, the ability to distinguish multiple labels on asingle specimen, and the ability to detect comparatively small numbersof targets in each cell. While these properties make fluorescence nearlyideal for automated imaging, the use of fluorescence in visualinterpretation is more limited due to bleaching, limited spectralresponse of the eye, and the limited dynamic range of the eye. Effortsto automate pathology have principally been guided by the staining andinterpretation methods used by the pathologist.

Software tools have been developed to automate the acquisition, andmanagement of images from tissue sections. For example, the BacusLaboratories, Inc. (Chicago, Ill.) has developed software to analyzetransmitted light tissue sections and tissue arrays along with softwaretools for image sharing and remote analysis.

Drug Discovery: On average, pharmaceutical companies spend more than $1billion to bring a new drug to market, yet despite this large investmentof time and resources, the frequency of drug failure is high. Poorefficacy and drug induced toxicity continue to be major causes of thesefailures [11, 12]. Furthermore, many candidate drugs fail late, inanimal testing or clinical testing, after significant investment indevelopment. Clearly, improved methods of functional assessment areneeded in drug discovery, as well as in other fields such asenvironmental health and industrial safety. Efficacy and toxicitystudies are carried out at several points during drug developmentincluding cell-based assays, ADME animal studies and clinical trials.Improvements in the reliability of tissue analysis are expected toimprove the reliability and safety of drug testing.

Personalized medicine: Genomics and proteomics have laid the groundworkfor diagnostic and therapeutic treatments that are customized for eachindividual patient. This personalized medicine is based on a systemsapproach to disease which takes into account a profile of the wholepatient, to determine the most effective therapy [2]. The molecularinformation derived from genomics and proteomics, and in particularthose genes and proteins that have been correlated with particulardisease conditions, often referred to as biomarkers, is certainly avaluable source of patient data, but the customization of the treatmentswill still be limited to well characterized classes of biomarkers, sincetherapies cannot be tested for every individual genome.

Environmental Toxicology: The challenge in environmental toxicology isto assess the impact of a growing list of natural and man-madesubstances on human health. Several factors complicate the problem:increasing large numbers of substances must be tested; the complexitiesof environmental exposure require testing over a broad range of exposuremechanism, concentration and time; and uncertainties regarding theinfluence of age and genetic variability on the results. Reliable meansto improve the efficiency of testing and evaluation are actively beingsought by the National Toxicology Program at the National Institutes ofHealth.

Biomedical research: Cell analysis is routinely used in basic biologicalresearch as well as in medical research. In both cases the cell analysisis usually focused on a single cellular process, as there are limitedtools available for analyzing complex, multi-component system responses.

Systems biology is an emerging research field focused on theinteractions between system components and pathways.

Functional Assessment: In vivo toxicology measures acute and chronictoxicity in several areas including mutagenicity, organ cytotoxicity,immunotoxicity, neurotoxicity, teratogenicity, and safety pharmacology.In vitro toxicology assays, such as CYP450 induction, Ames test, MTTassay and others, are used to measure these functional responses. Invitro toxicology assays are typically cell based assays which use avariety of cell types including hepatocytes, cardiomyocytes, and others.

Toxicogenomics uses a combination of traditional genetics and toxicologyto identify patterns of gene expression that are associated with toxiceffects. Toxicogenomics profiles typically include information such asnucleotide sequences, gene expression levels, protein synthesis, proteinfunction and some phenotypic responses. One goal of toxicogenomics is toidentify a sequence of genomic events that lead to a toxic biologicalresponse. [13].

Cell-Based Assays of Cytotoxicity: Existing cell based assays ofcytotoxicity are designed to detect a specific endpoint in a populationof cells. Examples include trypan blue staining, in which cell death isassessed microscopically by measuring the uptake of trypan blue dye thatis excluded by live cells. Other vital stains and fluorescentDNA-binding dyes which are also excluded from live cells can also beused. In another assay format, live cells are labeled with a probe whichis released upon cell death. Toxicity can also be assessed by measuringspecific cellular functions. One of the more common assays is the MTTassay, where cell proliferation is measured by the activity of amitochondrial enzyme. Other assays measure specific cellular markers.Examples include measurement of the activation of markers associatedwith the inflammation such as PGE-2, TNFα, IL1b and other interleukins.Assay formats can be in live cells, fixed cells or cell extracts. Manyof the same biomarkers used in these assays will be useful as componentsof a panel of tissue based cellular biomarkers.

Metabolism: Drug effect on metabolism is measured by radioactiveprecursor uptake, thymidine, uridine (or uracil for bacteria), and aminoacid, into DNA, RNA and proteins. Carbohydrate or lipid synthesis issimilarly measured using suitable precursors. Turnover of nucleic acidor protein, or the degradation of specific cell components, is measuredby prelabeling (or pulse labeling) followed by a purification step andquantitation of remaining label or sometimes by measurement of chemicalamounts of the component. Energy source metabolism is also analyzed foroptimal cell growth.

Light microscopy shows the general state of cells, and combined withtrypan blue exclusion, the percent of viable cells. Small, opticallydense cells indicate necrosis, while bloated “blasting” cells with blebsindicate apoptosis. Phase microscopy views cells in indirect light; thereflected light shows more detail, particularly intracellularstructures. Fluorescence microscopy detects individual components incells, after labeling with selective dyes or specific antibodies, andcan be used to identify cellular features associated with metabolicstates.

High Content Screening: High Content Screening (HCS) was developed as amethod whereby one or more cellular features are measured and analyzedin arrays of cells to identify a cellular functional response [5, 14,15]. For example, an HCS assay might be used to measure the activationof a particular receptor [16], mitochondrial activity [17], the onset ofapoptosis [5, 18], or another cellular function.

Each of these cellular features represents a measurement of particularcellular component. In some HCS assays a single cellular feature issufficient to indicate a single cellular function or response. In othercases, the measurement of several features is required to specificallyindicate a cellular response. For example, a commercial apoptosis assayuses four cell features to more specifically indicate apoptosis. Thesefeatures are interpreted based on the knowledge of the biology ofapoptosis.

Multiparameter cytotoxicity assays have been developed by nearly allvendors of HCS technologies. These assays are typically two to fourparameter assays which measure cellular features related to cell death,either by necrosis or apoptosis. These assays have been applied in drugdiscovery, and testing for environmental agents of biowarfare [19] oncultured cells and primary cell preparations. Many of the biomarkersused in HCS can also be used in combinations as components of a featurevector of cellular states in tissue sections and other tissue specimens.

Reagent Technologies: Multiple reagent technologies are available toassay cellular functions. Fluorescent reagent technologies have maturedover the last two decades, with probes available to labelsubcompartments, localize proteins, label membranes, respond to membranepotentials, sense the local chemical environment, read out molecularmobility, and provide many other measurements [20]. Coupled withantibodies, immunofluorescence labeling provides an easy method fordetecting and localizing proteins or protein variants such asphosphorylated proteins. Cells can be engineered to express proteinstagged with any of the color variants of fluorescent proteins [21, 22],and these fluorescent proteins can be further engineered to createbiosensors, indicators of specific cellular functions [16, 23-25]. Avariety of labels can be combined in a single sample preparation toprovide for the measurement of many features in each individual cell ina population, as well as in the population as a whole [10, 26]. Quantumdots, with their single excitation wavelength and narrow emission bands,provide the potential for even higher degrees of multiplexing within anassay [27]. In addition the rainbow of fluorescent probes, there are anumber of bioluminescent and chemiluminescent reagents that can beeffectively used in cell based assays [28, 29].

Multiparameter High Content Screening Profiles: A recent comparison ofthe performance of a panel of cytotoxicity assays, including DNAsynthesis, protein synthesis, glutathione depletion, superoxideinduction, Caspase-3 induction, membrane integrity and cell viabilityfound that these assays on average had only half the predictive power ofanimal studies [11]. In contrast, a relatively simple four parameterhigh content screening assay using human hepatocytes was found to bemore predictive than animal-based toxicity assays (O'Brien, P. J.;Irwin, W.; Diaz, D.; Howard-Cofield, E.; Krejsa, C. M.; Slaughter, M.R.; Gao, B.; Kaludercic, N.; Angeline, A.; Bernardi, P.; Brain, P.;Hougham, C., High concordance of drug-induced human hepatotoxicity within vitro cytotoxicity measured in a novel cell-based model using highcontent screening. Arch Toxicol 80:580-604 (2006)).

However, these assays were carried out independently, analyzed only forlowest active concentration, and no attempt was made to combine thereadouts in any quantitative way, to improve the overall predictivity.Several studies have shown that the multidimensional cellular responsesfrom cell-based assays can be clustered using standard methods, toidentify compounds with similar activities [10, 30, 31]. These studieshave demonstrated proof of principle for clustering compound responses,but have not attempted to correlate these identified clusters withspecific response profiles and then use the response to predict thephysiological impact of unknown substances. Similarly, multidimensionalcharacterization of cellular states in tissue or other specimens can beused to identify patterns of cellular states that are associated withspecific disease conditions or patient responses to treatment.

Classification Tools: A simple automated classifier has been developedfor use with some commercially available assays. This classifier allowsthe use of Boolean operations to combine the outputs from several assayfeatures into a single result [32]. These Boolean operations allow theassay developer to define an output that combines several featuremeasurements. This is useful in expanding the scope of some HCS assays,but has limited features, and is certainly not designed for, nor wouldit be easy to use with multidimensional feature sets.

Multiplexed Fluorescence for Cellular Systems Biology Profiling ofPatient Tissue Samples: The invention described herein is an improvedmethod for characterizing patient tissue specimens based on theintegration of specific fluorescence labeling technologies with imageacquisition and image analysis to create tissue marker profiles. Theinvention also discloses the use of the profiles to classify tissuespecimens for the purposes of identifying patient medical conditions,such as tumor staging and other disease states, as well as response totreatment.

One aspect of this invention is the integration of the use oftraditional histological staining and transmitted light-based imagingwith panels of molecularly specific, fluorescently labeled biomarkers tocorrelate morphometric interpretations with biomarker multiplexing in a“cellular systems biology profile.” The outcome is a powerfulmachine-learning platform where the instrument is fast and the softwareis simple.

A number of instruments are available for transmitted light imaging oftissue sections. For example, the Hamamatsu (Bridgewater, N.J.)NanoZoomer instrument allows automated processing of many slides perday. A number of instruments are available for fluorescent imaging ofslides, including confocal microscope, wide-field imaging, and HCSsystems. Both wide-field imaging systems and HCS systems can furthermake use of software deconvolution or structured illumination methods toimprove resolution of features in the sections. Therefore, bothtraditional and more powerful, molecularly specific fluorescentreporters can be imaged in tissue sections on slides or in microplates.

FIG. 3 illustrates the relationships between Systems Biology, Cellularsystems biology, cellomics, Genomics, Proteomics and Metabolomics.Systems biology is the study of an organism, viewed as an integrated andinteracting network of components, starting with genes, proteins, andbiochemical pathways, that give rise to life. Because biological systemsare complex, emergent properties result from interactions between systemcomponents. These emergent properties are properties that are notpredicted from component properties, but are the result of interactionsbetween components, and therefore require a systems approach tomeasurement and analysis.

Cellular systems biology is the study of the cell as the basic unit oflife: an integrated and interacting network of genes, proteins andbiochemical reactions which give rise to functions and life. The cell isthe simplest functional biological system, and therefore an ideal systemfrom which to extract knowledge about biological systems. Cellularsystems biology involves the application of cellular analysistechnologies to the understanding of how the interactions of cellularcomponents gives rise to the complex biochemical and molecular processesthat contribute to cell functions. These cell functions include complexbehavioral responses of cells to environmental changes as well asexperimental treatments. As illustrated in FIG. 3 Cellular systemsbiology is a component of Systems Biology.

The present invention relates to a method for identifying biologicalconditions in higher level organisms, including humans, from“systems-based” panel or panels of measurements of cellular and/ortissue features in tissue preparations, including blood, includingsections, smears and other cellular tissue preparations. The“systems-based” panel of measurements within the same samplesdramatically extends the present methodology that focuses on individualor a few parameters to the measurement and subsequent analysis of thesystems response profile from the tissue investigated. The methods ofthis invention also provide a means to quantify the similarity ofbiological states and predicted modes of action based on the tissuesystem profiles. There are many applications which will benefit from theuse of this invention, including animal testing in drug discovery andenvironmental health, medical diagnostics and human clinical trials.Application of this technology will improve the efficiency and reducethe cost of drug development. The invention will also improve theefficiency of environmental toxicology testing.

The invention includes various embodiments such as protocols, reagentpanels, databases and informatics software.

FIG. 5 illustrates an example of an embodiment of the invention whichcomprises a panel of assay function classes used to profile toxicity.These function classes include Stress Pathways, Organelle Function, CellCycle Stage, Morphology Changes, Apoptosis and DNA Damage. Otherfunction classes can be used in toxicity assessment and other functionalapplications of this method, as will be appreciated by a person of skillin the art. The methods of this invention can be used to validateadditional assays and function classes which can be added to a profileto improve the sensitivity, specificity or range of applicability of aspecific embodiment of this invention.

Within each of these assay function classes, one or more assays areselected to be used to measure one or more cellular systems biologyfeatures of cells within a tissue as an indication of a response in thatassay function class. To illustrate how cellular systems biology featuremeasurements can be made on cells or tissues, a similar high contentscreening assay with multiple features for cells in arrays isillustrated in FIG. 6. In this example assay, representative images fromeach channel of a multiplexed high content screen are shown. Algorithmsare used to extract information from the images to produce outputs of atleast four different cell features including nuclear size and shape,cell cycle distribution, DNA degradation, the state of the microtubulecytoskeleton, the activation state of the tumor suppressor p53, and thephosphorylation state of histone H3, a protein involved in theregulation of the cell cycle. Assays can be combined in two or moreassay plates to produce a compound profile with six or more features.Assays such as this, which include image analysis algorithms withmultiple output features are available from a variety of commercialsources, especially HCS technology vendors such as Cellomics(Pittsburgh, Pa.), GE Healthcare (Piscataway, N.J.), Molecular Devices(Sunnyvale, Calif.), and others, and can be implemented in any one ofthe standard image analysis software packages. The output features fromthe combination of assays, both commercial and custom developed, arecombined to form a single response profile. In one embodiment, assaysare selected from at least about four of the function classes in FIG. 5,to provide a sufficiently broad profile for predicting higher levelintegrated functions. One embodiment of this invention employs a panelof assays with one from each of these function classes. These assays areused first to build a predictive toxicology knowledgebase, and then togenerate profiles of test compounds, to compare with the classes in theknowledgebase, and thereby to predict toxic affects of the testsubstances. Another embodiment of the invention uses all the assayslisted in FIG. 5 to produce a more extensive profile, and then uses astatistical method such as principle components analysis to identify thefeatures with the highest predictive power for a selected profile oftoxicology parameters.

In some profiles multiple cell types are identified and analyzed to morebroadly indicate tissue associated responses. In addition, analyses caninclude combinations of assays where individual tissue cells aremeasured, along with higher throughput assays where the population oftissue cells or a region of a tissue section is analyzed as a whole formorphometry, texture, intensity, or other features, as will beappreciated by a person of skill in the art.

FIGS. 7 and 8 illustrate a flow diagram for two embodiments of theinvention. The procedures in FIGS. 7 and 8 illustrate separateprocedures. The procedure in FIG. 7 illustrates the procedure used topopulate the tissue profile database and create the classes of responseprofiles linked to the histological determinations. The procedure inFIG. 8 illustrates the process for using the profile database to predictthe classify tissue and identify medical states. The procedure in FIG. 8comprises the following steps: 1. Tissue samples are prepared on slidesor other carriers. 2. The tissues sections are fixed and stained withlabels specific to the biomarker of interest. 3. The slides are read onan imaging system, such as an HCS reader, high throughput slide-scanreader, automated microscope or other detector. 4. Assay algorithms areapplied to convert raw image data to assay data points. 5. The assaydata points are clustered to produce response classes. 6. Responsesclasses are used to create a response profile for each of the classes.7. Response profiles are established for the cells in control tissuespecimens in each slide set. 8. Response profiles are clustered toidentify unique profiles which can be used to classify and predictfunctional responses.

The procedure illustrated in FIG. 8 is used to evaluate substances forphysiological effects. It comprises a sequence of steps: 1. Samples areprepared on slides or other carriers. 2. The cells are fixed and stainedwith labels specific to the biomarker of interest. 3. The plates areread on an imaging system, such as an HCS reader, high throughputslide-scan reader, automated microscope or other detector. 4. Assayalgorithms are applied to convert raw image data to assay data points.5. The tissue cell features are classified based on the assay datapoints. 6. The database is searched for physiological response profilesthat match the cellular response profiles. 7. Predictions forphysiological responses are made based on similarity of responseprofiles. 8. A report is generated tabulating the probability of eachphysiological response based on the substance response data.

FIG. 7 illustrates the overall sample flow while processing tissuesections to produce cellular systems biology profiles. A slide setcomprises two or more tissue sections, each of which is used to collecta cellular systems biology profile. Each tissue section in the setproduces an image set of images from one or more fields in each tissuesection, at each of the wavelengths to be analyzed. Analysis of theimage set produces a set of cellular systems biology features. Thecellular systems biology features are processed and clustered to producea cellular systems biology profiles to go into the data base, or to beused to search the data base to identify probable modes of physiologicalresponse or to set priorities for patient stratification.

Populations of cells within tissues can occupy discrete responseclasses, and move from class to class as a disease or treatmentproceeds. In one example cellular systems biology profiles can be builtthrough the application of Kolmogorov-Smirnov (KS) similarity analysis.KS values are one means to characterize a population and provide ameasurement that can be used to cluster samples from many patients orother tissue sources. For example, cellular systems biology featuresbased on KS values can be clustered by agglomerative clustering or otherclustering methods, to build cellular systems biology profiles thatidentify tissues with similar cellular systems biology profiles. Othermethods in addition to KS analysis can be used to process data prior toclustering, and a variety of clustering algorithms can be usefullyapplied.

FIG. 8 illustrates one embodiment of the invention, wherein the dataflow is used to generate response profiles for a panel of tissue samplesor tissue assays. Tissue samples from sources with known conditions ormedical outcomes are processed to produce cellular response profiles,which are merged with other information on physiological conditions. Thecombined profiles of each tissue are clustered to identify uniqueprofiles that can be used to distinguish classes of response. Theresponse classes are stored in a database for use in classifying testsamples. Test tissue samples are processed to produce cellular responseprofiles that are then matched to those in the database, and based onthe similarity of the response to the database profiles, probabilitiesare calculated for each of the reference response profiles in thedatabase, producing a similarity profile.

Algorithms: The algorithms, custom designed or encapsulated in theapplication software provided by HCS vendors, or other imaging softwareproviders, produce multiple numerical feature values (cellular systemsbiology features) such as subcellular object intensities, shapes, andlocation for each cell within an optical field. The vHCS™ DiscoveryToolbox (Cellomics, Inc), Metamorph (Molecular Devices), software fromGE Healthcare and other HCS and image analysis packages can be used tobatch analyze images following acquisition. Contingent on the type oftissue sample and its preparation, the total number of cells measuredper sample is typically in the range of at least about 100 to at leastabout 10000, depending on the heterogeneity of the cellular response andthe sensitivity of the assay. Examples of assay output parametersillustrate the function of application software. For example, tocalculate changes in nuclear morphology, the average nuclear intensityvalue for each cell can be used. Nuclear condensation produces largeraverage nuclear intensity values while nuclear enlargement accompaniedby DNA degradation produced smaller average nuclear intensity valuesrelative to normal cells. The measurement of histone H3 phosphorylationis obtained using the average nuclear intensity of cells labeled withantibodies specific for phosphohistone H3 as previously reported. Thoseskilled in the art of imaging and cell analysis will recognize thatthere are many such algorithms readily available, and that there aremany such cellular processes that are amenable to image-based analysisof cells and tissues to measure cellular/tissue functions.

Clustering and Classification of Responses: To quantify differences inthe cellular systems biology feature responses induced in a populationof tissue cells, such as healthy tissue, tumor tissue, and otherabnormal tissues, several different methods can be effectively used.Within a population of similar cells or collections of cells in tissues,many different individual cellular response profiles are possible,including the well known heterogeneity in cellular responses [33, 34].In one embodiment, the cellular systems biology feature responsedistribution for each cell parameter from a tissue section can becompared with that of a control sample using a KS goodness of fitanalysis (KS value) [35]. The testing for significant changes influorescence-derived histograms is used to calculate KS values forreplicate control samples and use these data to set a threshold (e.g.,critical value), above which, a cellular systems biology featureresponse would be considered significant [36].

To perform significance testing of disease or therapy dependent changesor patient-specific differences in tissue features in multiplexedtissue-derived cell population distribution data, the one-dimensional KStest can be adapted to two dimensions as described by Peacock [37] andfurther refined by Fasano and Franceschini [38]. The two-dimensionalcell population data distributions representing two physiologicalparameters from a cellular systems biology feature set are compared tothe two-dimensional cell population data distributions obtained frommultiple specimens. First, each distribution is divided into quadrantsdefined by the median x and y axis values calculated from the untreatedcell data distributions. The two-dimensional KS value was then found byranging through all four quadrants to find the maximal differencebetween the fraction of cells in each treated quadrant and the fractionof cells in each corresponding untreated quadrant.

The heterogeneity of cell populations within tissues can also beanalyzed with other statistical methods to evaluate cellular systemsbiology profiles. In another embodiment of the invention, all the cellfeature values from each cell are combined to create a cellular systemsbiology profile. The cellular systems biology profiles can consist ofthe actual measured values, and/or the principal components of themeasured values, identified by standard methods [39, 40]. The cellularsystems biology features from each population of tissue cells and fromdifferent samples are clustered using standard methods [39, 40], toproduce cellular systems biology profiles. These profiles are used tobuild a classifier. All the cells in a single tissue sample, andtherefore characteristic of the same medical condition, are classifiedinto these response classes. The percent occupation of each of theseclasses then becomes a population response profile for that sample. Inone example, the cellular systems biology profiles from the samples arelinked to the cellular systems biology profiles (e.g., toxicity responseprofiles) from the reference samples and stored in the database. Thecellular systems biology profiles from the test samples are classifiedusing a probabilistic classifier based on the cellular systems biologyprofiles of the reference samples in the database to predicttoxicological responses or to stratify patients. Other embodiments usealternative analysis algorithms or methods to cluster cell responseprofiles and create a classifier based on the known properties of atraining set of tissue sections.

Examples

Example of tissue sample profiling of normal, diseased, and treatedtissues in humans and animals using liver as a specific tissue example:

The liver, a gland comprised of a host of cell types, performs bothexocrine and endocrine functions that are regulated by exquisitelyorchestrated cellular activities. Furthermore, the liver is alsoresponsible for the metabolism of drugs and steroids, many of whichtarget their toxic activities to one or more cell types present in theliver. Other important functions of the liver include deiodination oftriiodothyronine and thyroxine, gluconeogenesis and glycogenolysis,maintenance of normal glucose concentration in blood, etherification offree fatty acids into triglycerides, storage of glycogen, fat, and iron,detoxification of poisons and hydrogen peroxide, and hematopoiesis fromthe second to the eighth month of intrauterine life.

Thus, a cellular systems biology characterization of cells within theintact structure of the liver provides one of the most relevant profilesof normal or diseased tissue, and the effects that chemical compoundshave on the liver as a living system.

The intact liver, like other glands, is comprised of a stroma and ahighly vascularized and innervated parenchyma. Tissue sections of liverwill therefore be comprised of several cell types including:

1. Squamous epithelial cells and fibroblasts—form part of the stroma

2. Nerve fibers—cellular processes that accompany blood vessels toinnervate the parenchyma

3. Capillary endothelium—cells forming the walls of blood vessels

4. Kupfer cells—specialized macrophages

5. Fat cells—store triglycerides

6. Blood cells—cells that include erythrocytes, immune cells, andplatelets

7. Hepatocytes—the most prevalent cell type in the liver. Hepatocytesperform most of the functions of the liver listed above.

Rationale for combining traditional transmitted light microscopy andmultiplexed fluorescence based cytology of tumor sections: 1.Pathologists directly involved in test. 2. Allows direct comparison withpresent visual inspection of H&E stained sections as well as sectionslabeled with other manually detectable histochemical stains. 3.Maintains tissue organization and permits analysis of penetrating immunecells. 4. Allows implementation of automated imaging quantitation of thesystem. 5. Allows correlation of the presence and state of activation ofthe migratory immune cells with the presence and state of activation ofthe immune cells in the lymph nodes and peripheral blood. 6. Tissuetoxicity profiles can be produced from either/or tissue-based profilesor peripheral blood profiles based on the tissue-based profile data. 7.The multiplexed, fluorescence-based biomarkers can be a combination ofspecific reagents to detect specific proteins and post-translationalmodifications of the proteins, specific RNA species including coding ornon-coding RNA's, and micro-RNA's.

Below is a list of biomarkers that can be combined in variouscombinations to profile the systems response of liver tissue to diseaseor compound treatment:

1. Metabolism biomarkers:

-   -   Cytochrome P450 isotypes—expression levels and isotype ratios in        hepatocytes.    -   P-glycoprotein activity—expression level of a membrane-bound        protein that pumps multiple compound substrates out of a cell,        especially hepatocytes.

2. DNA damage biomarkers:

-   -   Cell cycle regulation—The distribution of the total DNA content        within the nucleus of a cell contained within a tissue slice can        be determined using a nuclear label such as Hoechst 33342,        Draq-5, or propidium iodide.    -   Nuclear morphology and chromatin condensation—Nuclear damage can        sometimes be correlated with a change in nuclear morphology or        the condensation state of the chromatin. The morphology (e.g.,        shape and size) or the structure of the chromatin (brightness        per unit area) of a nucleus contained within a tissue slice can        be determined using a nuclear label such as Hoechst 33342,        Draq-5, or propidium iodide.    -   8-oxoguanine—Oxidative damage to DNA often generates an oxidized        analog of guanine Increased 8-oxoguanine signals that the DNA in        a cell has been damaged.    -   Activation of DNA repair proteins (APE/ref-1)—The DNA in        hepatocytes or any other cells present in liver that contain DNA        are susceptible to damage due to disease or compound treatment.        Changes in the expression level of APE/ref-1 signals that the        DNA damage response mechanism has been activated within a cell.    -   Histone H2A.X phosphorylation—The DNA in hepatocytes or any        other cells present in liver that contain DNA are susceptible to        damage due to disease or compound treatment. Phosphorylation of        histone H2A.X signals that the DNA damage response mechanism has        been activated within a cell.    -   p53 protein activation.    -   Rb protein phosphorylation

3. Cell morphology and differentiation biomarkers:

-   -   Cell spreading and hypertrophy    -   Cell-cell or cell-stroma adhesion    -   Angiogenesis of new vessels    -   Remodeling of innervating nerve fibers

4. Stress-induced transcription factor activation or inhibitionbiomarkers:

-   -   NF-B    -   ATF-2    -   CREB    -   AP-1    -   MSK    -   NFAT    -   Stat1, 2, 3    -   Oct-1

5. Changes in phosphorylation state of stress kinases biomarkers:

-   -   ERK    -   JNK    -   p38    -   RSK90    -   MEK

6. Induction of apoptosis or necrosis biomarkers:

-   -   DNA content and degradation    -   Nuclear morphology    -   Caspase activation (multiple subtypes)    -   Mitochondrial function (mass-potential)    -   Bax mitochondrial translocation    -   Cytochrome c mitochondrial release    -   PARP activation

7. Remodeling of the cytoskeleton biomarkers:

-   -   Actin cytoskeleton stability    -   Microtubule cytoskeleton stability

8. Organelle morphology biomarkers:

-   -   Mitochondrial size, number, and shape    -   Golgi size and localization    -   Peroxisome size and number    -   Glycogen particle size and number    -   Lysosome size and number    -   Lipid droplet size and number    -   Endoplasmic reticulum shape and localization    -   Tight junction number and localization

9. Immune cell presence and activity biomarkers:

-   -   The percentage and ratios of specific migratory immune cells in        hepatocytes, lymph system, and blood supply.    -   Phenotypes of key immune cell types in liver cancer tissues that        reflect either an anti-tumor or tumor-supporting function.    -   Apoptosis of immune cells    -   Expression of death receptor ligands such as TRAIL    -   Expression of biomarkers associated with immune cell dysfunction        such as PD1 in lymphocytes    -   NK and LAK cell activity to characterize anti-tumor surveillance

Example of tissue preparation: In one embodiment, a small animal such asa mouse or a rat is treated with one or more test compounds for variouslengths of time (1 min to 21 d). In another embodiment, a small animalmodel of disease including metabolic models such as diabetes, cancer, orother models that either directly or indirectly involve the liver willbe used. In yet another embodiment, human liver tissue from diseased orcompound treated patients will be used. Normal, diseased, and treatedtissue samples will be prepared. Tissue samples will be processed aseither frozen sections or formaldehyde fixed paraffin-embedded sections.In addition, tissue samples will also be obtained for gene expressionanalysis.

For clarity, other major tissue types will be treated the same way.Panels of biomarkers of both a general cell responses and responses moretissue-specific will be produced and applied.

The optimal combination (multiplexing) of the liver tissue biomarkers,will be the key to creating an optimal cellular systems biology profileof the tissue. The optimal number of number of multiplexed biomarkerswill range from about four to about twelve biomarkers. Normal, diseased,and treated tissue samples will be prepared. Tissue samples will beprocessed as either frozen sections or formaldehyde fixedparaffin-embedded sections. In addition, tissue samples will also beobtained for gene expression analysis.

1. Below is an example of liver tissue analysis:

a. Gene expression profiling is performed that compares “normal” livertissue with tissues from diseased or compound treated animals.

b. Gene expression informatics—Gene expression profiles analyzed byinformatics tools to characterize gene expression as a function ofdisease or compound treatment to identify gene products.

c. Gene products prioritized based on known reference points from normalliver tissue and then antibodies acquired or produced to create testpanels.

2. Combinations of histological stains and key biomarkers multiplexedfor fluorescence-based immunocytochemistry of the “functionalbiomarkers”:

a. Multiple 5 μm sections prepared from liver tissue. The first sectionlabeled with H&E or other histological stain for traditionalpathological analysis. The successive sections processed formultiplexed, fluorescence-based cytometry.

b. In addition to the panels of potential biomarkers based on the geneexpression profiling, some sections will be labeled with multiplexedpanels of antibodies to key migratory immune cells; includinglymphocytes (e.g. CD3 and CD8). The level of immune cell activation,concentration and organization will be an important element of theprofile.

Example biomarker combinations to profile liver tissues: In oneembodiment, liver tissue slices are labeled for two or more biomarkersto profile differences between non-diseased and diseased or non-treatedand treated animals. Biomarkers of a wide range of tissue functions arepreferable since they provide breadth to the systems profile of thetissue. The number of biomarkers in one embodiment is about four toabout ten biomarkers, and multiple biomarkers can be labeled in the sametissue section. This permits the comparison of some biomarker activitieswithin the same cells.

In one example, a rat is treated with an apoptosis-inducing compoundsuch as paclitaxel or camptothecin for times ranging from about 30 minto about 21 d using multiple doses in the range from about 1 μg/kg up toabout 100 mg/kg. After treatment, the animal is sacrificed and the livertissue either frozen and sectioned or fixed with a chemical such asformaldehyde and then impregnated with paraffin using standard methodsbefore sectioning. A hematoxylin and eosin (H&E) stain can then beperformed on one or more sections to provide a sample for traditional,transmitted light-based pathology interpretation. Other sequentialsections can be labeled with combinations of fluorescent immunoreagentsand physiological indicator dyes for image-based analysis, for example:

Sequential Section #1

1. Hoechst 33342 to label the nuclei and provide measurements of nuclearmorphology, cell cycle regulation, and chromatin condensation.

2. Anti-phospho-histone H2A.X as a biomarker of oxidative DNA damage

3. Anti-p53 as a biomarker of the DNA damage response.

4. Anti-phospho-c-jun as a biomarker of stress kinase induction.

Sequential Section #2

1. Hoechst 33342

2. Anti-cytochrome c as a biomarker of mitochondrial number, size andshape.

3. Anti-alpha-tubulin as a biomarker of microtubule cytoskeletalremodeling.

4. Fluorescently labeled phalloidin as a biomarker of actin cytoskeletalremodeling.

Sequential Section #3

1. Hoechst 33342

2. Anti-phospho-retinoblastoma protein as a biomarker of cell cyclecheckpoint activity.

3. Anti-NF-kappa-B as a biomarker of inflammation-related cellsignaling.

4. Anti-CD3 as a biomarker of lymphocyte infiltration into the tissue.

Sequential Section #4

1. Hoechst 33342

2. Anti-activated-caspase 3 as a biomarker of apoptosis.

3. Anti-PMP70 as a biomarker of peroxisome size and number.

4. Anti-cytochrome P450 as a biomarker of hepatocyte metabolic activity.

Example of Patient Sample Profiling for Breast Cancer: Cancer is asystems biology disease that requires a systems biology approach tocreate better stratification of individual patients for betterdiagnostics and treatments. Cancer is also an inflammatory process thatinvolves the full range of the immune response. Therefore, tumorscontain a combination of cancer cells at different stages of evolution,normal cells and an infiltration of the migratory immune cells such asdendritic cells, macrophages and lymphocytes. Tumor “cellular systemsbiology” characterization should therefore be a combination of tumorcell biomarkers and immune cell biomarkers. A key to tumor cellularsystems biology is the use of a multiplexed panel of tumor biomarkersfor cancer cells and immune cells that will better stratify patients. Inaddition, correlations with lymph nodes and peripheral blood cellanalysis would determine if circulating immune cells carry tumorspecific information that could create a very simple blood cell test.The number, type and level of activation of migratory immune cells inthe blood could also become a “window” on the tumor itself.

Rationale for Combining Traditional Transmitted Light Microscopy andMultiplexed Fluorescence-Based Cytology of Tumor Sections: 1.Pathologists directly involved in test. 2. Allows direct correlationwith present visual inspection of H&E stained sections and stagingtumors by morphometric analyses. 3. Builds on the success of Her2/Neu asa single “functional protein” biomarker, but which also only identifiesa small sub-set of patients. 4. Maintains tissue organization andpermits analysis of penetrating immune cells. 5. Enables the developmentof a “systems” profile of the tumor including multiplexed breast cancerbiomarkers and migratory immune cell presence and state of activation.6. Allows implementation of automated imaging quantitation of thesystem. 7. Allows correlation of the presence and state of activation ofthe migratory immune cells with the presence and state of activation ofthe immune cells in the lymph nodes and peripheral blood. 8.Stratification and diagnostic tests can be produced from either/ortissue-based profiles or peripheral blood profiles based on thetissue-based profile data. 9. The multiplexed, fluorescence-basedbiomarkers can be a combination of specific reagents to detect specificproteins and post-translational modifications of the proteins, specificRNA species, including micro-RNA's either coding or non-coding in cells.

Measurement of specific protein expression and state of activation, aswell as the presence of specific micro RNA's within cells and tissuesare key “functional” read-outs. The expression of a gene is only oneelement of the systems biology and the present genomic tests are onlycorrelations of gene expression without any functional information.Cellular functions are carried out primarily by proteins whoseexpression level, cellular localization and post-translationalmodification are responsible for carrying out normal and abnormalfunctions. Specific microRNA's have also been shown to be diseasespecific and are critical in regulating gene expression, similar toregulatory proteins. In addition, tumors are systems in that they are acomplex integration of normal cells, a range of genetically evolvingcancer cells and migrating immune cells. Therefore, a cellular systemsbiology profile of multiple protein and/or micro RNA biomarkers isimportant.

Background on the Importance of the Immune System in Breast Cancer: Theimmune system becomes dysfunctional early in the process of canceroccurrence and continues throughout the evolution of the cancer stagesleading to metastatic disease. The migratory immune cells are attractedto the growing tumors by pro-inflammatory cytokines and chemotacticfactors. Tumor infiltrating lymphocytes release growth factors andcytokines that actually promote growth of the tumors, while theanti-tumor functions are weak or non-existent. Dendritic cells andtumor-associated macrophages present in the tumor exhibit phenotypesthat demonstrate a supporting role for tumor growth. Regulatory T cellsaccumulate in the tumors, as well as in the tumor-draining lymph nodesand peripheral blood of patients. These latter cells actually protecttumor cells as part of the “recognition of self” immune process.Therefore, the immune system is mostly a tumor-promoting system andsupports the progression and metastasis in most cancers.

Gene expression fingerprints from tumor samples have been used todistinguish subtypes of breast cancers and to assign some prognosticindex. These gene expression profiles usually identify genetic profile“signatures” indicative of the infiltration of the migratory immunecells. Unfortunately, in methods such as gene expression profiling, thedisaggregated tumor samples the “tumor as a system” is lost since thewhole tissue architecture and tumor cell-migratory immune cellstructural relationships are lost.

Tissue sections, including tissue micro-arrays (TMA's) used in patientstratification and diagnostic tests are valuable, since the tumor“system” can be analyzed and quantified through the integrated use oftraditional transmitted light stains that are standard in pathology andoncology with multiplexed fluorescence-based biomarkers of morefunctional parameters of both the migratory immune cells and the cancercells. Therefore, the traditional information from pathology can becombined with panels of biomarkers using multiplexed fluorescence.

In addition to the primary tumors, the tumor-draining and non-sentinellymph nodes are important sites of tumor and immune system interactionsthat could aid in the “functional cellular systems biology signature”.For example, the presence of tumor cells in the tumor-draining lymphnodes affects the types and numbers of immune cells within the nodes.Furthermore, the non-sentinel auxiliary nodes can also be influenced bylocal tumor growth, since it has been shown that CD4 T cells anddendritic cell counts have been used to predict survival in breastcancer patients. Also, it is clear that tumor progression also can beobserved in the peripheral immune system by analysis of the circulatingleukocytes, circulating T cells and other immune cells. Therefore, acorrelative analysis of the patient's circulating immune cells in theperipheral blood with the tumor “system”, as well as lymph node “system”will create the an excellent opportunity to create powerful tests intumors, lymph nodes and blood.

Below is a list of biomarkers that can be combined in variouscombinations for optimal staging and diagnostic for breast cancer (inone embodiment, the combination of cancer cell and immune biomarkers maybe most suitable):

Examples of Cancer Cell Biomarkers:

-   -   Her2/Neu Protein (now used as single biomarker)    -   Estrogen Receptor Protein (ER)    -   Ki-67    -   Cox-2    -   P16    -   A growing number of key proteins or post-translational        modifications of proteins correlated with a cancer process    -   A growing number of micro RNA's correlated with specific cancers

Examples of Immune Biomarkers:

-   -   The percentage and ratios of specific migratory immune cells in        tumors, tumor draining lymph nodes, non-sentinel lymph nodes and        peripheral blood    -   Phenotypes of key immune cell types in breast cancer patients        that reflect either an anti-tumor or tumor-supporting function    -   Apoptosis of immune cells    -   Expression of death receptor ligands such as TRAIL    -   Expression of biomarkers associated with immune cell dysfunction        such as PD1 in Tumor Infiltrating Lymphocytes.    -   NK and LAK cell activity to characterize anti-tumor surveillance

The optimal combination (also referred to herein as multiplexing) of thecancer cell and immune biomarkers, especially in the tumors, will be thedeterminative to creating an optimal cellular systems biology profile ofthe patient. In one embodiment, the optimal number of number ofmultiplexed biomarkers is in the range from about four to about twelvebiomarkers.

Technical Steps: Normal and breast cancer positive patient materialswill be prepared. Patient tumor samples will be processed as eitherfrozen sections or formaldehyde fixed paraffin-embedded sections.Furthermore, lymph node samples will be treated the same as the primarytumors. In addition, samples will be obtained from the tumors for geneexpression analysis. Migratory immune cells will also be separated fromthe blood samples for both flow cytometry and image cytometry. Below isan outline of steps in one method of the invention:

1. Patient Tumor Sample-Gene Expression Profiling comparing “normal”tissue with patient tumors staged in the traditional manner.

2. Gene Expression Informatics-Gene Expression Profiles analyzed byinformatics tools to characterize gene expression as a function of stageof breast cancer and to identify gene products (use Her2/Neu asreference).

3. Gene products prioritized based on known reference points includingHer2/Neu and then antibodies acquired or produced to create test panels.

4. Combinations of selected cancer cell biomarkers multiplexed forfluorescence-based immunohistochemistry.

5. Multiple 5 micron tissue sections prepared from tumor samples. Thefirst section labeled for H&E for traditional staging by a pathologist.The successive sections processed for multiplexed, fluorescence-basedcytometry.

6. In addition to the panels of potential cancer cell biomarkers basedon the gene expression profiling, some sections will be labeled withmultiplexed panels of antibodies to key migratory immune cells;including lymphocytes (e.g., CD3 and/or CD8). The level of immune cellactivation, concentration and organization will be an important elementof the profile.

The percentage and ratios of specific migratory immune cells in tumors,tumor draining lymph nodes, non-sentinel lymph nodes and peripheralblood will be calculated and used build cellular systems biologyprofiles. Example percentage ranges of immune cells in tissues are asfollows:

Lymphocytes: 1%-90% (distinct sub-types within this percentage)

Neutrophils: 1%-90%

Eosinophils: 0.01%-50%

Monocytes: 0.01%-50% (distinct sub-types within this percentage)

Example ranges of ratios of immune cells in tissues for cellular systemsbiology profiling:

T-cell lymphocyte subtype I/T-cell lymphocyte subtype II: 0.01-1000

T-cell lymphocytes/B-cell lymphocytes: 0.1-1000

Dendritic cells/lymphocytes: 0.01-1000

Macrophages/lymphocytes: 0.01-1000

Lymphocyte sub-set/lymphocyte sub-set: 0.01-1000

The optimal combination of biomarkers that suitably stratify patientsamples from stage I to stage IV will be selected for profiling on newpatients. New patients will allow the direct correlation of peripheralimmune cells with the tumor tissue and lymph node sections.

Example of profiling brain tissue for biomarkers of Alzheimer's disease:

In this embodiment, human brain tissue is obtained, fixed, andsectioned. A subset of sections are labeled with one or more stains tovisualize morphological structures within the tissue associated with thepathology of Alzheimer's disease. In one example, a silver-based stainis used to visualize hallmarks of Alzheimer's disease such as neuriteplaques and neurons with neurofibrillary tangles [41]. Analysis of thesilver-stained tissue from multiple patients before, during, or aftertreatments with drugs provides data which are then entered into aprofile.

In a second embodiment, another subset of the same tissue sections fromthe same patient is reacted with reagents to label two or morebiomarkers in either the same tissue section or in contiguous serialsections from the same tissue sample. Example biomarkers that can belabeled using immunofluorescence approaches include A 42, A 40, vonWillebrand factor, and the microtubule binding protein tau [42]. Otherbiomarkers are also possible. These include phosphorylated APP (amyloidprecursor protein) and unphosphorylated APP. Furthermore, biomarkers ofother cellular processes can be included in the profile. Profiles builtfrom multiple biomarker labels measured within tissues from a singlepatient or profiles built from biomarker labels measured in multiplepatient tissue samples are clustered to identify unique profiles thatcan be used to classify and predict possible patient outcomes, orfunctional responses to drug treatments, or a combination of both.

REFERENCES

-   1. Hood, L. and R. M. Perlmutter, The impact of systems approaches    on biological problems in drug discovery. Nat Biotechnol, 2004.    22(10): p. 1215-7.-   2. Hood, L., et al., Systems biology and new technologies enable    predictive and preventative medicine. Science, 2004. 306(5696): p.    640-3.-   3. Taylor, D. L., et al., Potential of machine-vision light    microscopy in toxicologic pathology. Toxicol Pathol, 1994. 22(2): p.    145-59.-   4. Schroeder, K. S. and B. D. Neagle, FLIPR: A New Instrument for    Accurate, High Throughput Optical Screening. J Biomol Screen, 1996.    1(2): p. 75-80.-   5. Giuliano, K. A., et al., High-Content Screening: A New Approach    to Easing Key Bottlenecks in the Drug Discovery Process. J Biomol    Screen, 1997. 2(4): p. 249-259.-   6. Dow, A., S. A. Shafer, and A. S. Waggoner. Morphological    segmentation of multiprobe fluorescence images for immunophenotyping    in melanoma tissue sections. in Intelligent Robots and Computer    Vision XII: Algorithms and Techniques. 1993: SPIE.-   7. Dow, A. I., et al., Automatic multiparameter fluorescence imaging    for determining lymphocyte phenotype and activation status in    melanoma tissue sections. Cytometry, 1996. 25(1): p. 71-81.-   8. Galbraith, W., et al., Imaging cytometry by multiparameter    fluorescence. Cytometry, 1991. 12(7): p. 579-96.-   9. Camp, R. L., G. G. Chung, and D. L. Rimm, Automated subcellular    localization and quantification of protein expression in tissue    microarrays. Nat Med, 2002. 8(11): p. 1323.-   10. Taylor, D. and K. Giuliano, Mutiplexed high content screening    assays create a cellular systems biology approach to drug discovery.    Drug Discov Today, 2005. 2(2): p. 149-154.-   11. Xu, J. J., D. Diaz, and P. J. O'Brien, Applications of    cytotoxicity assays and pre-lethal mechanistic assays for assessment    of human hepatotoxicity potential. Chem Biol Interact, 2004.    150(1): p. 115-28.-   12. Perlman, Z. E., T. J. Mitchison, and T. U. Mayer, High-Content    Screening and Profiling of Drug Activity in an Automated    Centrosome-Duplication Assay. Chembiochem, 2005. 6(2): p. 218.-   13. Lee, K. M., J. H. Kim, and D. Kang, Design issues in    toxicogenomics using DNA microarray experiment. Toxicol Appl    Pharmacol, 2005.-   14. Abraham, V. C., D. L. Taylor, and J. R. Haskins, High content    screening applied to large-scale cell biology. Trends    Biotechnol, 2004. 22(1): p. 15-22.-   15. Giuliano, K. A., J. R. Haskins, and D. L. Taylor, Advances in    high content screening for drug discovery. Assay Drug Dev    Technol, 2003. 1(4): p. 565-77.-   16. Conway, B. R. and K. T. Demarest, The use of biosensors to study    GPCR function: applications for high-content screening. Receptors    Channels, 2002. 8(5-6): p. 331-41.-   17. Woollacott, A. J. and P. B. Simpson, High Throughput    Fluorescence Assays for the Measurement of Mitochondrial Activity in    Intact Human Neuroblastoma Cells. J Biomol Screen, 2001. 6(6): p.    413-420.-   18. Lovborg, H., P. Nygren, and R. Larsson, Multiparametric    evaluation of apoptosis: effects of standard cytotoxic agents and    the cyanoguanidine CHS 828. Mol Cancer Ther, 2004. 3(5): p. 521-6.-   19. Tencza, S. B. and M. A. Sipe, Detection and classification of    threat agents via high-content assays of mammalian cells. J Appl    Toxicol, 2004. 24(5): p. 371-7.-   20. Waggoner, A., Fluorescence probes for analysis of cell    structure, function and health by flow and imaging cytometry., in    Applications of Fluorescence in the Biomedical Sciences, D. Taylor,    et al., Editors. 1986, Alan R. Liss, Inc.: New York. p. 3-28.-   21. Chalfie, M., et al., Green fluorescent protein as a marker for    gene expression. Science, 1994. 263(5148): p. 802-5.-   22. Chudakov, D. M., S. Lukyanov, and K. A. Lukyanov, Fluorescent    proteins as a toolkit for in vivo imaging. Trends Biotechnol, 2005.    23(12): p. 605-13.-   23. Umezawa, Y., Genetically encoded optical probes for imaging    cellular signaling pathways. Biosens Bioelectron, 2005. 20(12): p.    2504-11.-   24. Giuliano, K. A. and D. L. Taylor, Fluorescent-protein    biosensors: new tools for drug discovery. Trends Biotechnol, 1998.    16(3): p. 135-40.-   25. Giuliano, K. A. and D. L. Taylor, Measurement and manipulation    of cytoskeletal dynamics in living cells. Curr Opin Cell Biol, 1995.    7(1): p. 4-12.-   26. Zhang, S., C. Ma, and M. Chalfie, Combinatorial marking of cells    and organelles with reconstituted fluorescent proteins. Cell, 2004.    119(1): p. 137-44.-   27. Michalet, X., et al., Quantum dots for live cells, in vivo    imaging, and diagnostics. Science, 2005. 307(5709): p. 538-44.-   28. Hemmila, I. and V. Laitala, Progress in lanthanides as    luminescent probes. J Fluoresc, 2005. 15(4): p. 529-42.-   29. Roda, A., et al., Biotechnological applications of    bioluminescence and chemiluminescence. Trends Biotechnol, 2004.    22(6): p. 295-303.-   30. Mitchison, T. J., Small-molecule screening and profiling by    using automated microscopy. Chembiochem, 2005. 6(1): p. 33-9.-   31. Perlman, Z. E., et al., Multidimensional drug profiling by    automated microscopy. Science, 2004. 306(5699): p. 1194-8.-   32. Abraham, V. C., et al., Automated Classification of Individual    Cellular Responses Across Multiple Targets. Preclinica, 2004.    2(5): p. 349-355.-   33. Rubin, H., Early origin and pervasiveness of cellular    heterogeneity in some malignant transformations. Proc Natl Acad Sci    USA, 1984. 81(16): p. 5121-5.-   34. Elsasser, W. M., Outline of a theory of cellular heterogeneity.    Proc Natl Acad Sci USA, 1984. 81(16): p. 5126-9.-   35. Giuliano, K. A., et al., Systems cell biology knowledge created    from high content screening. Assay Drug Dev Technol, 2005. 3(5): p.    501-14.-   36. Giuliano, K. A., Y.-T. Chen, and D. L. Taylor, High-Content    Screening with siRNA Optimizes a Cell Biological Approach to Drug    Discovery: Defining the Role of P53 Activation in the Cellular    Response to Anticancer Drugs. J Biomol Screen, 2004. 9(7): p.    557-568.-   37. Peacock, J. A., Two-dimensional goodness-of-fit testing in    astronomy. Monthly Notices of the Royal Astronomical Society, 1983.    202: p. 615-627.-   38. Fasano, G. and A. Franceschini, A multidimensional version of    the Kolmogorov-Smirnov test. Monthly Notices of the Royal    Astronomical Society, 1987. 225: p. 155-170.-   39. Witten, I. H. and E. Frank, Data Mining: Practical Machine    Learning Tools and Techniques. Second ed. Morgan Kaufmann Series in    Data Management Systems, ed. J. Gray. 2005, San Francisco, Calif.:    Elsevier. 523.-   40. Venables, W. N., B. D. Ripley, and W. N. Venables, Modern    applied statistics with S. 4th ed. Statistics and computing. 2002,    New York: Springer. xi, 495 p.-   41. Switzer, R. C., III, S. K. Campbell, and L. Murdock,    Histological analysis method. 1993: USA.-   42. Uchihara, T., et al., Triple immunofluorolabeling with two    rabbit polyclonal antibodies and a mouse monoclonal antibody    allowing three-dimensional analysis of cotton wool plaques in    Alzheimer disease. J Histochem Cytochem, 2003. 51(9): p. 1201-6.-   43. Strategic analysis of the ADME/Tox technologies market in    Europe. 2005, Frost and Sullivan.

The teachings of all patents, published applications and referencescited herein are incorporated by reference in their entirety.

While this invention has been particularly shown and described withreferences to example embodiments thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the scope of the inventionencompassed by the appended claims.

What is claimed is:
 1. A method for producing a cellular systems biologyprofile of one or more tissue samples comprising: a) obtaining at leasttwo sections from one or more tissue samples; b) labeling at least onesection with a histological stain, thereby producing a histologicallystained section; c) labeling at least one section with a panel offluorescently labeled reagents, thereby producing a fluorescentlylabeled section, wherein each fluorescently labeled reagent is specificfor a biomarker, and wherein the panel of fluorescently labeled reagentsdetects at least four different biomarkers, and wherein the detection ofa biomarker is a read-out of one or more features of a cellular systemsbiology profile; d) imaging the histologically stained section with atleast a first optical mode, wherein the imaging produces a first set ofdata; e) imaging the fluorescently labeled section with at least asecond optical mode, wherein the imaging produces a second set of data;f) analyzing the first set of data and the second set of data toidentify five or more features, wherein at least one feature isidentified in each of the first set of data and the second set of data,and wherein the combination of the five or more features generates acellular systems biology profile of the one or more tissue samples,wherein at least the steps of e) and f) are automated, thereby providinga method for producing a cellular systems biology profile of the one ormore tissue samples.
 2. The method of claim 1, wherein the methodfurther comprises comparing the cellular systems biology profiles of twoor more tissue samples, thereby identifying similarities, differences,or combinations thereof, of the two or more tissue samples.
 3. Themethod of claim 1, wherein two or more tissue samples are isolated froma human patient at one or more time points, wherein at least one tissuesample is isolated from each time point from the human patient.
 4. Themethod of claim 1, wherein the histological stain is selected from thegroup consisting of alcian blue, Fuchsin, haematoxylin and eosin (H&E),Masson trichrome, toluidine blue, Wright's/Giemsa stain, andcombinations thereof.
 5. The method of claim 1, wherein the panel offluorescently labeled reagents is selected from the group consisting offluorescently labeled antibodies, fluorescently labeled peptides,fluorescently labeled proteins, fluorescently labeled aptamers,fluorescently labeled oligonucleotides, fluorescently labeled chemicals,fluorescent chemicals, and combinations thereof.
 6. The method of claim1, wherein the panel of fluorescently labeled reagents indicate thepresence, amount, location, activity, distribution, or combinationthereof, of the biomarkers in the fluorescently labeled section.
 7. Themethod of claim 1, wherein the method further comprises comparing thereference cellular systems biology profile in the database with acellular systems biology profile of one or more further samples, therebyidentifying similarities, differences, or a combination thereof, of thecellular systems biology profile of the one or more further samples andthe reference cellular systems biology profile.
 8. The method of claim7, wherein the cellular systems biology profile of the one or morefurther samples and the cellular systems biology profile in the databaseare compared using one or more of a graphical display, cluster analysis,or statistical measure of correlation.
 9. The method of claim 1, furthercomprising producing a cellular systems biology profile of at least oneperipheral blood sample obtained from the same source as the one or moretissue samples, comprising: i) obtaining at least one blood sample smearfrom at least one peripheral blood sample; ii) labeling the at least oneblood sample smear with a panel of fluorescently labeled reagents,thereby producing a fluorescently labeled blood sample smear, whereineach fluorescently labeled reagent is specific for a biomarker, andwherein the panel of fluorescently labeled reagents detects at leastfour different biomarkers, and wherein the detection of a biomarker is aread-out of one or more features of a cellular systems biology profile;iii) imaging the fluorescently labeled blood sample smear with at leasta third optical mode, wherein the imaging produces a third set of data;iv) analyzing the third set of data to identify five or more features,wherein the five or more features is a cellular systems biology profileof the at least one blood sample smear, thereby producing a cellularsystems biology profile of the at least one peripheral blood sampleobtained from the same source as the one or more tissue samples.
 10. Themethod of claim 1, further comprising producing a cellular systemsbiology profile of one or more peripheral blood samples obtained fromthe same source as the one or more tissue samples, comprising: i)obtaining at least two blood sample smears from one or more peripheralblood samples; ii) labeling at least one blood sample smear with ahistological stain, producing a histologically stained blood samplesmear; iii) labeling at least one blood sample smear with a panel offluorescently labeled reagents, thereby producing a fluorescentlylabeled blood sample smear, wherein each fluorescently labeled reagentis specific for a biomarker, and wherein the panel of fluorescentlylabeled reagents detects at least four different biomarkers, and whereinthe detection of a biomarker is a read-out of one or more features of acellular systems biology profile; iv) imaging the histologically stainedblood sample smear with at least a third optical mode, wherein theimaging produces a third set of data; v) imaging the fluorescentlylabeled blood sample smear with at least a fourth optical mode, whereinthe imaging produces a fourth set of data; vi) analyzing the third setof data and the fourth set of data to identify five or more features,wherein at least one feature is identified in each of the third set ofdata and the fourth set of data, and wherein the combination of the fiveor more features is a cellular systems biology profile of the one ormore blood sample smears, thereby producing a cellular systems biologyprofile of the one or more peripheral blood samples obtained from thesame source as the one or more tissue samples.
 11. A method forproducing a cellular systems biology profile of one or more tissuesamples comprising: a) obtaining at least one section from one or moretissue samples; b) labeling the at least one section with a panel offluorescently labeled reagents, thereby producing a fluorescentlylabeled section, wherein each fluorescently labeled reagent is specificfor a biomarker, and wherein the panel of fluorescently labeled reagentsdetects at least four different biomarkers, and wherein the detection ofa biomarker is a read-out of one or more features of a cellular systemsbiology profile; c) imaging the fluorescently labeled section with atleast a first optical mode, wherein the imaging produces a first set ofdata; d) analyzing the first set of data to identify five or morefeatures, wherein at least one feature is identified in the first set ofdata, and wherein the combination of the five or more features is acellular systems biology profile the one or more tissue samples, whereinat least the steps of e) and f) are automated, thereby providing amethod for cellular systems biology profiling of the one or more tissuesamples.
 12. The method of claim 11, further comprising producing acellular systems biology profile of at least one peripheral blood sampleobtained from the same source as the one or more tissue samples,comprising: i) obtaining at least one blood sample smear from at leastone peripheral blood sample; ii) labeling the at least one blood samplesmear with a panel of fluorescently labeled reagents, thereby producinga fluorescently labeled blood sample smear, wherein each fluorescentlylabeled reagent is specific for a biomarker, and wherein the panel offluorescently labeled reagents detects at least four differentbiomarkers, and wherein the detection of a biomarker is a read-out ofone or more features of a cellular systems biology profile; iii) imagingthe fluorescently labeled blood sample smear with at least a secondoptical mode, wherein the imaging produces a second set of data; iv)analyzing the second set of data to identify five or more features,wherein the five or more features is a cellular systems biology profileof the at least one blood sample smear, thereby producing a cellularsystems biology profile of the at least one peripheral blood sampleobtained from the same source as the one or more tissue samples.
 13. Themethod of claim 11, further comprising producing a cellular systemsbiology profile of one or more peripheral blood samples obtained fromthe same source as the one or more tissue samples, comprising: i)obtaining at least two blood sample smears from one or more peripheralblood samples; ii) labeling at least one blood sample smear with ahistological stain, producing a histologically stained blood samplesmear; iii) labeling at least one blood sample smear with a panel offluorescently labeled reagents, thereby producing a fluorescentlylabeled blood sample smear, wherein each fluorescently labeled reagentis specific for a biomarker, and wherein the panel of fluorescentlylabeled reagents detects at least four different biomarkers, and whereinthe detection of a biomarker is a read-out of one or more features of acellular systems biology profile; iv) imaging the histologically stainedblood sample smear with at least a second optical mode, wherein theimaging produces a second set of data; v) imaging the fluorescentlylabeled blood sample smear with at least a third optical mode, whereinthe imaging produces a third set of data; vi) analyzing the second setof data and the third set of data to identify five or more features,wherein at least one feature is identified in each of the second set ofdata and the third set of data, and wherein the combination of the fiveor more features is a cellular systems biology profile of the one ormore blood sample smears, thereby producing a cellular systems biologyprofile of the one or more peripheral blood samples obtained from thesame source as the one or more tissue samples.
 14. A method forproducing a cellular systems biology profile of one or more tissuesamples, wherein the tissue sample is profiled for the presence ofcancer, the stage of a cancer, the diagnosis of a cancer, the prognosisof a cancer, or combination thereof, comprising: a) obtaining at leasttwo sections from one or more tissue samples, wherein the one or moretissue samples is selected from the group consisting a suspectedcancerous tissue, a lymph node, and a combination thereof; b) labelingat least one section with a histological stain, thereby producing ahistologically stained section; c) labeling at least one section with apanel of fluorescently labeled reagents, thereby producing afluorescently labeled section, wherein each fluorescently labeledreagent is specific for a biomarker, and wherein the panel offluorescently labeled reagents comprises fluorescently labeled reagentsselected from the group consisting of: i) a set of fluorescently labeledreagents specific for at least four cancer cell biomarkers; ii) a set offluorescently labeled reagents specific for at least four migratoryimmune cell biomarkers; iii) a combination of: A) a set of fluorescentlylabeled reagents specific for at least three cancer cell biomarkers; andB) a set of fluorescently labeled reagents specific for at least threemigratory immune cell biomarkers; and iv) combinations thereof, whereinthe panel of fluorescently labeled reagents detects at least fourdifferent biomarkers, and wherein the detection of a biomarker is aread-out of one or more features of a cellular systems biology profile;d) imaging the histologically stained section with at least a firstoptical mode, wherein the imaging produces a first set of data; e)imaging the fluorescently labeled section with at least a second opticalmode, wherein the imaging produces a second set of data; f) analyzingthe first set of data and second set of data to identify five or morefeatures, wherein at least one feature is identified in each of thefirst set of data and the second set of data, and wherein thecombination of the five or more features is a cellular systems biologyprofile of the one or more tissue samples, thereby providing a methodfor producing a cellular systems biology profile of the one or moretissue samples, wherein the tissue sample is profiled for the presenceof a cancer, the stage of a cancer, the diagnosis of a cancer, theprognosis of a cancer or combination thereof.
 15. The method of claim14, further comprising producing a cellular systems biology profile ofat least one peripheral blood sample obtained from the same source asthe one or more tissue samples, comprising: i) obtaining at least oneblood sample smear from at least one peripheral blood sample; ii)labeling the at least one blood sample smear with a panel offluorescently labeled reagents, thereby producing a fluorescentlylabeled blood sample smear, wherein each fluorescently labeled reagentis specific for a biomarker, and wherein the panel of fluorescentlylabeled reagents detects at least four different biomarkers, and whereinthe detection of a biomarker is a read-out of one or more features of acellular systems biology profile; iii) imaging the fluorescently labeledblood sample smear with at least a third optical mode, wherein theimaging produces a third set of data; iv) analyzing the third set ofdata to identify five or more features, wherein the five or morefeatures is a cellular systems biology profile of the at least one bloodsample smear, thereby producing a cellular systems biology profile ofthe at least one peripheral blood sample obtained from the same sourceas the one or more tissue samples.
 16. The method of claim 15, whereinthe at least one peripheral blood sample is taken at the same ordifferent time point as the one or more tissue samples are obtained. 17.The method of claim 14, further comprising producing a cellular systemsbiology profile of one or more peripheral blood samples obtained fromthe same source as the one or more tissue samples, wherein the tissuesample is profiled for presence of cancer, the stage of a cancer, thediagnosis of a cancer, the prognosis of a cancer or a combinationthereof, comprising: a) obtaining at least two blood sample smears fromone or more peripheral blood samples; b) labeling at least one bloodsample smear with a histological stain, thereby producing ahistologically stained blood sample smear; c) labeling at least oneblood sample smear with a panel of fluorescently labeled reagents,thereby producing a fluorescently labeled blood sample smear, whereineach fluorescently labeled reagent is specific for a biomarker, andwherein the panel of fluorescently labeled reagents detects at leastfour different biomarkers, and wherein the detection of a biomarker is aread-out of one or more features of a cellular systems biology profile;d) imaging the histologically stained blood sample smear with at least athird optical mode, wherein the imaging produces a third set of data; e)imaging the fluorescently labeled blood sample smear with at least afourth optical mode, wherein the imaging produces a fourth set of data;f) analyzing the third set of data and the fourth set of data toidentify five or more features, wherein at least one feature isidentified in each of the third set of data and the fourth set of data,and wherein the combination of the five or more features is a cellularsystems biology profile of the one or more blood sample smears, therebyproducing a cellular systems biology profile of one the or moreperipheral blood samples obtained from the same source as the one ormore tissue samples, wherein the tissue sample is profiled for thepresence or absence of a cancer, the stage of a cancer, the diagnosis ofa cancer, the prognosis of a cancer or a combination thereof.
 18. Themethod of claim 17, wherein the one or more peripheral blood samples aretaken at the same or different time points as the one or more tissuesamples are obtained.
 19. The method of claim 14, wherein at least thesteps of d), e) and f) are automated.
 20. A method for producing acellular systems biology profile of one or more tissue samples, whereinthe tissue sample is profiled for the presence, severity or absence of atissue toxicity, comprising: a) obtaining at least two sections from oneor more tissue samples; b) labeling at least one section with ahistological stain, thereby producing a histologically stained section;c) labeling at least one section with a panel of fluorescently labeledreagents, thereby producing a fluorescently labeled section, whereineach fluorescently labeled reagent is specific for a biomarker, andwherein the panel of fluorescently labeled reagents comprises a set offluorescently labeled reagents selected from the group consisting of: i)one or more fluorescently labeled reagents specific for cell metabolismbiomarkers; ii) one or more fluorescently labeled reagents specific forDNA damage biomarkers; iii) one or more fluorescently labeled reagentsspecific for cell morphology biomarkers; iv) one or more fluorescentlylabeled reagents specific for DNA damage biomarkers; v) one or morefluorescently labeled reagents specific for cell differentiationbiomarkers; vi) one or more fluorescently labeled reagents specific forstress-induced transcription activation or inhibition biomarkers; vii)one or more fluorescently labeled reagents specific for phosphorylationstatus of stress kinase biomarkers; viii) one or more fluorescentlylabeled reagents specific for apoptosis or necrosis biomarkers; ix) oneor more fluorescently labeled reagents specific for cytoskeletonbiomarkers; x) one or more fluorescently labeled reagents specific fororganelle biomarkers; xi) one or more fluorescently labeled reagentsspecific for presence or activation of immune cell biomarkers; and xii)combinations thereof, wherein the panel of fluorescently labeledreagents detects at least four different biomarkers, and wherein thedetection of a biomarker is a read-out of one or more features of acellular systems biology profile; d) imaging the histologically stainedsection with at least a first optical mode, wherein the imaging producesa first set of data; e) imaging the fluorescently labeled section withat least a second optical mode, wherein the imaging produces a secondset of data; f) analyzing the first set of data and second set of datato identify five or more features, wherein at least one feature isidentified in each of the first set of data and the second set of data,and wherein the combination of the five or more features is a cellularsystems biology profile of the one or more tissue samples, wherein atleast the steps of d), e) and f) are automated, thereby providing amethod for producing a cellular systems biology profile of the one ormore tissue samples, wherein the tissue sample is profiled for thepresence, severity or absence of a tissue toxicity.
 21. The method ofclaim 20, wherein the one or more tissue samples is one or more livertissue samples.